The application of chemical leasing business models in Mexico.

Science.gov (United States)

Schwager, Petra; Moser, Frank

2006-03-01

To better address the requirements of the changing multilateral order, the United Nations Industrial Development Organization (UNIDO) Cleaner Production Programme, in 2004, developed the new Sustainable Industrial Resource Management (SIRM) approach. This approach is in accordance with the principles decided at the United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro, Brazil in 1992. Unlike the traditional approaches to environmental management, the SIRM concept captures the idea of achieving sustainable industrial development through the implementation of circular material and energy flows in the entire production chain and reduction of the amount of material and energy used with greater efficiency solutions. The SIRM approach seeks to develop new models to encourage a shift from selling products to supplying services, modifying, in this manner, the supplier/user relationship and resulting in a win-win situation for the economy and the environment. Chemical Leasing represents such a new service-oriented business model and is currently being promoted by UNIDO's Cleaner Production Programme. MAIN FEATURES. One of the potential approaches to address the problems related to ineffective use and over-consumption of chemicals is the development and implementation of Chemical Leasing business models. These provide concrete solutions to the effective management of chemicals and on the ways negative releases to the environment can be reduced. The Chemical Leasing approach is a strategy that addresses the obligations of the changing international chemicals policy by focusing on a more service-oriented strategy. Mexico is one of the countries that were selected for the implementation of UNIDO's demonstration project to promote Chemical Leasing models in the country. The target sector of this project is the chemical industry, which is expected to shift their traditional business concept towards a more service and value-added approach. This is

A Chemical Activity Approach to Exposure and Risk Assessment of Chemicals

DEFF Research Database (Denmark)

Gobas, Frank A. P. C.; Mayer, Philipp; Parkerton, Thomas F.

2018-01-01

activity approach, its strengths and limitations, and provides examples of how this concept may be applied to the management of single chemicals and chemical mixtures. The examples demonstrate that the chemical activity approach provides a useful framework for 1) compiling and evaluating exposure......To support the goals articulated in the vision for exposure and risk assessment in the twenty-first century, we highlight the application of a thermodynamic chemical activity approach for the exposure and risk assessment of chemicals in the environment. The present article describes the chemical...... assessment. The article further illustrates that the chemical activity approach can support an adaptive management strategy for environmental stewardship of chemicals where “safe” chemical activities are established based on toxicological studies and presented as guidelines for environmental quality...

Multi-scale modeling for sustainable chemical production.

Science.gov (United States)

Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

2013-09-01

With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling chemical kinetics graphically

NARCIS (Netherlands)

Heck, A.

2012-01-01

In literature on chemistry education it has often been suggested that students, at high school level and beyond, can benefit in their studies of chemical kinetics from computer supported activities. Use of system dynamics modeling software is one of the suggested quantitative approaches that could

Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

Science.gov (United States)

Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

2015-11-01

Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

Science.gov (United States)

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

Chemical Topic Modeling: Exploring Molecular Data Sets Using a Common Text-Mining Approach.

Science.gov (United States)

Schneider, Nadine; Fechner, Nikolas; Landrum, Gregory A; Stiefl, Nikolaus

2017-08-28

Big data is one of the key transformative factors which increasingly influences all aspects of modern life. Although this transformation brings vast opportunities it also generates novel challenges, not the least of which is organizing and searching this data deluge. The field of medicinal chemistry is not different: more and more data are being generated, for instance, by technologies such as DNA encoded libraries, peptide libraries, text mining of large literature corpora, and new in silico enumeration methods. Handling those huge sets of molecules effectively is quite challenging and requires compromises that often come at the expense of the interpretability of the results. In order to find an intuitive and meaningful approach to organizing large molecular data sets, we adopted a probabilistic framework called "topic modeling" from the text-mining field. Here we present the first chemistry-related implementation of this method, which allows large molecule sets to be assigned to "chemical topics" and investigating the relationships between those. In this first study, we thoroughly evaluate this novel method in different experiments and discuss both its disadvantages and advantages. We show very promising results in reproducing human-assigned concepts using the approach to identify and retrieve chemical series from sets of molecules. We have also created an intuitive visualization of the chemical topics output by the algorithm. This is a huge benefit compared to other unsupervised machine-learning methods, like clustering, which are commonly used to group sets of molecules. Finally, we applied the new method to the 1.6 million molecules of the ChEMBL22 data set to test its robustness and efficiency. In about 1 h we built a 100-topic model of this large data set in which we could identify interesting topics like "proteins", "DNA", or "steroids". Along with this publication we provide our data sets and an open-source implementation of the new method (CheTo) which

Computer-Aided Multiscale Modelling for Chemical Process Engineering

DEFF Research Database (Denmark)

Morales Rodriguez, Ricardo; Gani, Rafiqul

2007-01-01

Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework...

A Decision Analytic Approach to Exposure-Based Chemical ...

Science.gov (United States)

The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in suppor

Design of tailor-made chemical blend using a decomposition-based computer-aided approach

DEFF Research Database (Denmark)

Yunus, Nor Alafiza; Gernaey, Krist; Manan, Z.A.

2011-01-01

Computer aided techniques form an efficient approach to solve chemical product design problems such as the design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product...... methodology for blended liquid products that identifies a set of feasible chemical blends. The blend design problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model where the objective is to find the optimal blended gasoline or diesel product subject to types of chemicals...... and their compositions and a set of desired target properties of the blended product as design constraints. This blend design problem is solved using a decomposition approach, which eliminates infeasible and/or redundant candidates gradually through a hierarchy of (property) model based constraints. This decomposition...

Improvement of the Correlative AFM and ToF-SIMS Approach Using an Empirical Sputter Model for 3D Chemical Characterization.

Science.gov (United States)

Terlier, T; Lee, J; Lee, K; Lee, Y

2018-02-06

Technological progress has spurred the development of increasingly sophisticated analytical devices. The full characterization of structures in terms of sample volume and composition is now highly complex. Here, a highly improved solution for 3D characterization of samples, based on an advanced method for 3D data correction, is proposed. Traditionally, secondary ion mass spectrometry (SIMS) provides the chemical distribution of sample surfaces. Combining successive sputtering with 2D surface projections enables a 3D volume rendering to be generated. However, surface topography can distort the volume rendering by necessitating the projection of a nonflat surface onto a planar image. Moreover, the sputtering is highly dependent on the probed material. Local variation of composition affects the sputter yield and the beam-induced roughness, which in turn alters the 3D render. To circumvent these drawbacks, the correlation of atomic force microscopy (AFM) with SIMS has been proposed in previous studies as a solution for the 3D chemical characterization. To extend the applicability of this approach, we have developed a methodology using AFM-time-of-flight (ToF)-SIMS combined with an empirical sputter model, "dynamic-model-based volume correction", to universally correct 3D structures. First, the simulation of 3D structures highlighted the great advantages of this new approach compared with classical methods. Then, we explored the applicability of this new correction to two types of samples, a patterned metallic multilayer and a diblock copolymer film presenting surface asperities. In both cases, the dynamic-model-based volume correction produced an accurate 3D reconstruction of the sample volume and composition. The combination of AFM-SIMS with the dynamic-model-based volume correction improves the understanding of the surface characteristics. Beyond the useful 3D chemical information provided by dynamic-model-based volume correction, the approach permits us to enhance

Modelling stratospheric chemistry in a global three-dimensional chemical transport model

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M [Finnish Meteorological Inst., Sodankylae (Finland). Sodankylae Observatory

1996-12-31

Numerical modelling of atmospheric chemistry aims to increase the understanding of the characteristics, the behavior and the evolution of atmospheric composition. These topics are of utmost importance in the study of climate change. The multitude of gases and particulates making up the atmosphere and the complicated interactions between them affect radiation transfer, atmospheric dynamics, and the impacts of anthropogenic and natural emissions. Chemical processes are fundamental factors in global warming, ozone depletion and atmospheric pollution problems in general. Much of the prevailing work on modelling stratospheric chemistry has so far been done with 1- and 2-dimensional models. Carrying an extensive chemistry parameterisation in a model with high spatial and temporal resolution is computationally heavy. Today, computers are becoming powerful enough to allow going over to 3-dimensional models. In order to concentrate on the chemistry, many Chemical Transport Models (CTM) are still run off-line, i.e. with precalculated and archived meteorology and radiation. In chemistry simulations, the archived values drive the model forward in time, without interacting with the chemical evolution. This is an approach that has been adopted in stratospheric chemistry modelling studies at the Finnish Meteorological Institute. In collaboration with the University of Oslo, a development project was initiated in 1993 to prepare a stratospheric chemistry parameterisation, fit for global 3-dimensional modelling. This article presents the parameterisation approach. Selected results are shown from basic photochemical simulations

Modelling stratospheric chemistry in a global three-dimensional chemical transport model

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M. [Finnish Meteorological Inst., Sodankylae (Finland). Sodankylae Observatory

1995-12-31

Numerical modelling of atmospheric chemistry aims to increase the understanding of the characteristics, the behavior and the evolution of atmospheric composition. These topics are of utmost importance in the study of climate change. The multitude of gases and particulates making up the atmosphere and the complicated interactions between them affect radiation transfer, atmospheric dynamics, and the impacts of anthropogenic and natural emissions. Chemical processes are fundamental factors in global warming, ozone depletion and atmospheric pollution problems in general. Much of the prevailing work on modelling stratospheric chemistry has so far been done with 1- and 2-dimensional models. Carrying an extensive chemistry parameterisation in a model with high spatial and temporal resolution is computationally heavy. Today, computers are becoming powerful enough to allow going over to 3-dimensional models. In order to concentrate on the chemistry, many Chemical Transport Models (CTM) are still run off-line, i.e. with precalculated and archived meteorology and radiation. In chemistry simulations, the archived values drive the model forward in time, without interacting with the chemical evolution. This is an approach that has been adopted in stratospheric chemistry modelling studies at the Finnish Meteorological Institute. In collaboration with the University of Oslo, a development project was initiated in 1993 to prepare a stratospheric chemistry parameterisation, fit for global 3-dimensional modelling. This article presents the parameterisation approach. Selected results are shown from basic photochemical simulations

Chemical Leasing business models and corporate social responsibility.

Science.gov (United States)

Moser, Frank; Jakl, Thomas; Joas, Reihard; Dondi, Francesco

2014-11-01

Chemical Leasing is a service-oriented business model that shifts the focus from increasing sales volume of chemicals towards a value-added approach. Recent pilot projects have shown the economic benefits of introducing Chemical Leasing business models in a broad range of sectors. A decade after its introduction, the promotion of Chemical Leasing is still predominantly done by the public sector and international organizations. We show in this paper that awareness-raising activities to disseminate information on this innovative business model mainly focus on the economic benefits. We argue that selling Chemical Leasing business models solely on the grounds of economic and ecological considerations falls short of branding it as a corporate social responsibility initiative, which, for this paper, is defined as a stakeholder-oriented concept that extends beyond the organization's boundaries and is driven by an ethical understanding of the organization's responsibility for the impact of its business activities. For the analysis of Chemical Leasing business models, we introduce two case studies from the water purification and metal degreasing fields, focusing on employees and local communities as two specific stakeholder groups of the company introducing Chemical Leasing. The paper seeks to demonstrate that Chemical Leasing business models can be branded as a corporate social responsibility initiative by outlining the vast potential of Chemical Leasing to improve occupational health and safety and to strengthen the ability of companies to protect the environment from the adverse effects of the chemicals they apply.

Learning of Chemical Equilibrium through Modelling-Based Teaching

Science.gov (United States)

Maia, Poliana Flavia; Justi, Rosaria

2009-01-01

This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

Multi-scale modeling for sustainable chemical production

DEFF Research Database (Denmark)

Zhuang, Kai; Bakshi, Bhavik R.; Herrgard, Markus

2013-01-01

associated with the development and implementation of a su stainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow......With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes...... models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process...

Amazing variational approach to chemical reactions

OpenAIRE

Fernández, Francisco M.

2009-01-01

In this letter we analyse an amazing variational approach to chemical reactions. Our results clearly show that the variational expressions are unsuitable for the analysis of empirical data obtained from chemical reactions.

APPROACHES FOR INCORPORATING NON-CHEMICAL STRESSORS INTO CUMULATIVE RISK ASSESSMENTS

Science.gov (United States)

Over the past twenty years, the risk assessment paradigm has gradually shifted from an individual chemical approach to a community-based model. Inherent in community-based risk assessment is consideration of the totality of stressors affecting a defined population including both ...

An approach for assessing human exposures to chemical mixtures in the environment

International Nuclear Information System (INIS)

Rice, Glenn; MacDonell, Margaret; Hertzberg, Richard C.; Teuschler, Linda; Picel, Kurt; Butler, Jim; Chang, Young-Soo; Hartmann, Heidi

2008-01-01

Humans are exposed daily to multiple chemicals, including incidental exposures to complex chemical mixtures released into the environment and to combinations of chemicals that already co-exist in the environment because of previous releases from various sources. Exposures to chemical mixtures can occur through multiple pathways and across multiple routes. In this paper, we propose an iterative approach for assessing exposures to environmental chemical mixtures; it is similar to single-chemical approaches. Our approach encompasses two elements of the Risk Assessment Paradigm: Problem Formulation and Exposure Assessment. Multiple phases of the assessment occur in each element of the paradigm. During Problem Formulation, analysts identify and characterize the source(s) of the chemical mixture, ensure that dose-response and exposure assessment measures are concordant, and develop a preliminary evaluation of the mixture's fate. During Exposure Assessment, analysts evaluate the fate of the chemicals comprising the mixture using appropriate models and measurement data, characterize the exposure scenario, and estimate human exposure to the mixture. We also describe the utility of grouping the chemicals to be analyzed based on both physical-chemical properties and an understanding of environmental fate. In the article, we also highlight the need for understanding of changes in the mixture composition in the environment due to differential transport, differential degradation, and differential partitioning to other media. The section describes the application of the method to various chemical mixtures, highlighting issues associated with assessing exposures to chemical mixtures in the environment

[DIFFERENT APPROACHES FOR CHEMICAL RISK ASSESSMENT IN LABORATORIES].

Science.gov (United States)

Caporossi, Lidia; Papaleo, Bruno; Capanna, Silvia; Calicchia, Sara; Marcellini, Laura; De Rosa, Mariangela; Castellano, Paola

2015-01-01

The aim of this study was to compare the different approaches used for chemical risk assessment, in relation to the perception of riskfor operators, in some research laboratories of a hospital in Rome. All information regarding the chemicals used for the application of three algorithmic models for chemical risk assessment ("Movarisch", "Inforisk", "Archimede") were collected. An environmental and biological monitoring and a study on the combined exposure to multiple chemicals using the World Health Organization proposed steps were carried out. A questionnaire was prepared for the identification of risk perception. An estimation of chemical risk with algorithms was compared with data from monitoring: findings showed that estimated risk was higher than those identified with airborne or urine concentrations, always under their limit values. The study of multiple exposure showed a possible cumulative risk, in some cases, but the conditions of use (volume and time) often bring to a reduced one. The perception of risk attributed to the monitored hazardous substances showed a correct perception in all laboratories and for all workers, with regard to the substances manipulated.

Coupling between solute transport and chemical reactions models

International Nuclear Information System (INIS)

Samper, J.; Ajora, C.

1993-01-01

During subsurface transport, reactive solutes are subject to a variety of hydrodynamic and chemical processes. The major hydrodynamic processes include advection and convection, dispersion and diffusion. The key chemical processes are complexation including hydrolysis and acid-base reactions, dissolution-precipitation, reduction-oxidation, adsorption and ion exchange. The combined effects of all these processes on solute transport must satisfy the principle of conservation of mass. The statement of conservation of mass for N mobile species leads to N partial differential equations. Traditional solute transport models often incorporate the effects of hydrodynamic processes rigorously but oversimplify chemical interactions among aqueous species. Sophisticated chemical equilibrium models, on the other hand, incorporate a variety of chemical processes but generally assume no-flow systems. In the past decade, coupled models accounting for complex hydrological and chemical processes, with varying degrees of sophistication, have been developed. The existing models of reactive transport employ two basic sets of equations. The transport of solutes is described by a set of partial differential equations, and the chemical processes, under the assumption of equilibrium, are described by a set of nonlinear algebraic equations. An important consideration in any approach is the choice of primary dependent variables. Most existing models cannot account for the complete set of chemical processes, cannot be easily extended to include mixed chemical equilibria and kinetics, and cannot handle practical two and three dimensional problems. The difficulties arise mainly from improper selection of the primary variables in the transport equations. (Author) 38 refs

Quantum chemical approach to estimating the thermodynamics of metabolic reactions.

Science.gov (United States)

Jinich, Adrian; Rappoport, Dmitrij; Dunn, Ian; Sanchez-Lengeling, Benjamin; Olivares-Amaya, Roberto; Noor, Elad; Even, Arren Bar; Aspuru-Guzik, Alán

2014-11-12

Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism.

Chemical kinetics and combustion modeling

Energy Technology Data Exchange (ETDEWEB)

Miller, J.A. [Sandia National Laboratories, Livermore, CA (United States)

1993-12-01

The goal of this program is to gain qualitative insight into how pollutants are formed in combustion systems and to develop quantitative mathematical models to predict their formation rates. The approach is an integrated one, combining low-pressure flame experiments, chemical kinetics modeling, theory, and kinetics experiments to gain as clear a picture as possible of the process in question. These efforts are focused on problems involved with the nitrogen chemistry of combustion systems and on the formation of soot and PAH in flames.

Ecological risk assessment of mixtures of radiological and chemical stressors: Methodology to implement an msPAF approach

International Nuclear Information System (INIS)

Beaumelle, Léa; Della Vedova, Claire; Beaugelin-Seiller, Karine; Garnier-Laplace, Jacqueline; Gilbin, Rodolphe

2017-01-01

A main challenge in ecological risk assessment is to account for the impact of multiple stressors. Nuclear facilities can release both radiological and chemical stressors in the environment. This study is the first to apply species sensitivity distribution (SSD) combined with mixture models (concentration addition (CA) and independent action (IA)) to derive an integrated proxy of the ecological impact of combined radiological and chemical stressors: msPAF (multisubstance potentially affected fraction of species). The approach was tested on the routine liquid effluents from nuclear power plants that contain both radioactive and stable chemicals. The SSD of ionising radiation was significantly flatter than the SSD of 8 stable chemicals (namely Cr, Cu, Ni, Pb, Zn, B, chlorides and sulphates). This difference in shape had strong implications for the selection of the appropriate mixture model: contrarily to the general expectations the IA model gave more conservative (higher msPAF) results than the CA model. The msPAF approach was further used to rank the relative potential impact of radiological versus chemical stressors. - Highlights: • msPAF methodology was applied on mixtures of radiological and chemical stressors. • A consistent set of chronic SSDs was collected for ionising radiation and 8 stable chemicals. • The SSD of ionising radiation had lower steepness than the SSD of stable chemicals. • This resulted in higher msPAF values based on the IA than on the CA mixture model. - The msPAF approach combining SSD and mixture models was used for the first time on mixtures of radiological and chemical stressors.

Engineered Barrier System: Physical and Chemical Environment Model

International Nuclear Information System (INIS)

Jolley, D. M.; Jarek, R.; Mariner, P.

2004-01-01

The conceptual and predictive models documented in this Engineered Barrier System: Physical and Chemical Environment Model report describe the evolution of the physical and chemical conditions within the waste emplacement drifts of the repository. The modeling approaches and model output data will be used in the total system performance assessment (TSPA-LA) to assess the performance of the engineered barrier system and the waste form. These models evaluate the range of potential water compositions within the emplacement drifts, resulting from the interaction of introduced materials and minerals in dust with water seeping into the drifts and with aqueous solutions forming by deliquescence of dust (as influenced by atmospheric conditions), and from thermal-hydrological-chemical (THC) processes in the drift. These models also consider the uncertainty and variability in water chemistry inside the drift and the compositions of introduced materials within the drift. This report develops and documents a set of process- and abstraction-level models that constitute the engineered barrier system: physical and chemical environment model. Where possible, these models use information directly from other process model reports as input, which promotes integration among process models used for total system performance assessment. Specific tasks and activities of modeling the physical and chemical environment are included in the technical work plan ''Technical Work Plan for: In-Drift Geochemistry Modeling'' (BSC 2004 [DIRS 166519]). As described in the technical work plan, the development of this report is coordinated with the development of other engineered barrier system analysis model reports

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

Directory of Open Access Journals (Sweden)

Matteo Pappalardo

Full Text Available The human histamine H4 receptor (hH4R, a member of the G-protein coupled receptors (GPCR family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE and Iterative Stochastic Elimination (ISE approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

Science.gov (United States)

Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

Science.gov (United States)

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Chemical modeling of waste sludges

International Nuclear Information System (INIS)

Weber, C.F.; Beahm, E.C.

1996-10-01

The processing of waste from underground storage tanks at the Oak Ridge National Laboratory (ORNL) and other facilities will require an understanding of the chemical interactions of the waste with process chemicals. Two aspects of sludge treatment should be well delineated and predictable: (1) the distribution of chemical species between aqueous solutions and solids, and (2) potential problems due to chemical interactions that could result in process difficulties or safety concerns. It is likely that the treatment of waste tank sludge will begin with washing, followed by basic or acidic leaching. The dissolved materials will be in a solution that has a high ionic strength where activity coefficients are far from unity. Activity coefficients are needed in order to calculate solubilities. Several techniques are available for calculating these values, and each technique has its advantages and disadvantages. The techniques adopted and described here is the Pitzer method. Like any of the methods, prudent use of this approach requires that it be applied within concentration ranges where the experimental data were fit, and its use in large systems should be preceded by evaluating subsystems. While much attention must be given to the development of activity coefficients, other factors such as coprecipitation of species and Ostwald ripening must also be considered when one aims to interpret results of sludge tests or to predict results of treatment strategies. An understanding of sludge treatment processes begins with the sludge tests themselves and proceeds to a general interpretation with the aid of modeling. One could stop with only data from the sludge tests, in which case the table of data would become an implicit model. However, this would be a perilous approach in situations where processing difficulties could be costly or result in concerns for the environment or health and safety

Engineered Barrier System: Physical and Chemical Environment Model

Energy Technology Data Exchange (ETDEWEB)

D. M. Jolley; R. Jarek; P. Mariner

2004-02-09

The conceptual and predictive models documented in this Engineered Barrier System: Physical and Chemical Environment Model report describe the evolution of the physical and chemical conditions within the waste emplacement drifts of the repository. The modeling approaches and model output data will be used in the total system performance assessment (TSPA-LA) to assess the performance of the engineered barrier system and the waste form. These models evaluate the range of potential water compositions within the emplacement drifts, resulting from the interaction of introduced materials and minerals in dust with water seeping into the drifts and with aqueous solutions forming by deliquescence of dust (as influenced by atmospheric conditions), and from thermal-hydrological-chemical (THC) processes in the drift. These models also consider the uncertainty and variability in water chemistry inside the drift and the compositions of introduced materials within the drift. This report develops and documents a set of process- and abstraction-level models that constitute the engineered barrier system: physical and chemical environment model. Where possible, these models use information directly from other process model reports as input, which promotes integration among process models used for total system performance assessment. Specific tasks and activities of modeling the physical and chemical environment are included in the technical work plan ''Technical Work Plan for: In-Drift Geochemistry Modeling'' (BSC 2004 [DIRS 166519]). As described in the technical work plan, the development of this report is coordinated with the development of other engineered barrier system analysis model reports.

Computational Approaches to Chemical Hazard Assessment

Science.gov (United States)

Luechtefeld, Thomas; Hartung, Thomas

2018-01-01

Summary Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models. PMID:29101769

Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

Science.gov (United States)

Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

2008-06-01

A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

A systems engineering approach to manage the complexity in sustainable chemical product-process design

DEFF Research Database (Denmark)

Gani, Rafiqul

This paper provides a perspective on model-data based solution approaches for chemical product-process design, which consists of finding the identity of the candidate chemical product, designing the process that can sustainably manufacture it and verifying the performance of the product during...... application. The chemical product tree is potentially very large and a wide range of options exist for selecting the product to make, the raw material to use as well as the processing route to employ. It is shown that systematic computer-aided methods and tools integrated within a model-data based design...

Approaches to chemical synthetic biology.

Science.gov (United States)

Chiarabelli, Cristiano; Stano, Pasquale; Anella, Fabrizio; Carrara, Paolo; Luisi, Pier Luigi

2012-07-16

Synthetic biology is first represented in terms of two complementary aspects, the bio-engineering one, based on the genetic manipulation of extant microbial forms in order to obtain forms of life which do not exist in nature; and the chemical synthetic biology, an approach mostly based on chemical manipulation for the laboratory synthesis of biological structures that do not exist in nature. The paper is mostly devoted to shortly review chemical synthetic biology projects currently carried out in our laboratory. In particular, we describe: the minimal cell project, then the "Never Born Proteins" and lastly the Never Born RNAs. We describe and critically analyze the main results, emphasizing the possible relevance of chemical synthetic biology for the progress in basic science and biotechnology. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Development and Analysis of Group Contribution Plus Models for Property Prediction of Organic Chemical Systems

DEFF Research Database (Denmark)

Mustaffa, Azizul Azri

for the GIPs are then used in the UNIFAC model to calculate activity coefficients. This approach can increase the application range of any “host” UNIFAC model by providing a reliable predictive model towards fast and efficient product development. This PhD project is focused on the analysis and further......Prediction of properties is important in chemical process-product design. Reliable property models are needed for increasingly complex and wider range of chemicals. Group-contribution methods provide useful tool but there is a need to validate them and improve their accuracy when complex chemicals...... are present in the mixtures. In accordance with that, a combined group-contribution and atom connectivity approach that is able to extend the application range of property models has been developed for mixture properties. This so-called Group-ContributionPlus (GCPlus) approach is a hybrid model which combines...

Include dispersion in quantum chemical modeling of enzymatic reactions: the case of isoaspartyl dipeptidase.

Science.gov (United States)

Zhang, Hai-Mei; Chen, Shi-Lu

2015-06-09

The lack of dispersion in the B3LYP functional has been proposed to be the main origin of big errors in quantum chemical modeling of a few enzymes and transition metal complexes. In this work, the essential dispersion effects that affect quantum chemical modeling are investigated. With binuclear zinc isoaspartyl dipeptidase (IAD) as an example, dispersion is included in the modeling of enzymatic reactions by two different procedures, i.e., (i) geometry optimizations followed by single-point calculations of dispersion (approach I) and (ii) the inclusion of dispersion throughout geometry optimization and energy evaluation (approach II). Based on a 169-atom chemical model, the calculations show a qualitative consistency between approaches I and II in energetics and most key geometries, demonstrating that both approaches are available with the latter preferential since both geometry and energy are dispersion-corrected in approach II. When a smaller model without Arg233 (147 atoms) was used, an inconsistency was observed, indicating that the missing dispersion interactions are essentially responsible for determining equilibrium geometries. Other technical issues and mechanistic characteristics of IAD are also discussed, in particular with respect to the effects of Arg233.

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

Science.gov (United States)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

LLNL Chemical Kinetics Modeling Group

Energy Technology Data Exchange (ETDEWEB)

Pitz, W J; Westbrook, C K; Mehl, M; Herbinet, O; Curran, H J; Silke, E J

2008-09-24

The LLNL chemical kinetics modeling group has been responsible for much progress in the development of chemical kinetic models for practical fuels. The group began its work in the early 1970s, developing chemical kinetic models for methane, ethane, ethanol and halogenated inhibitors. Most recently, it has been developing chemical kinetic models for large n-alkanes, cycloalkanes, hexenes, and large methyl esters. These component models are needed to represent gasoline, diesel, jet, and oil-sand-derived fuels.

Polarographic validation of chemical speciation models

International Nuclear Information System (INIS)

Duffield, J.R.; Jarratt, J.A.

2001-01-01

It is well established that the chemical speciation of an element in a given matrix, or system of matrices, is of fundamental importance in controlling the transport behaviour of the element. Therefore, to accurately understand and predict the transport of elements and compounds in the environment it is a requirement that both the identities and concentrations of trace element physico-chemical forms can be ascertained. These twin requirements present the analytical scientist with considerable challenges given the labile equilibria, the range of time scales (from nanoseconds to years) and the range of concentrations (ultra-trace to macro) that may be involved. As a result of this analytical variability, chemical equilibrium modelling has become recognised as an important predictive tool in chemical speciation analysis. However, this technique requires firm underpinning by the use of complementary experimental techniques for the validation of the predictions made. The work reported here has been undertaken with the primary aim of investigating possible methodologies that can be used for the validation of chemical speciation models. However, in approaching this aim, direct chemical speciation analyses have been made in their own right. Results will be reported and analysed for the iron(II)/iron(III)-citrate proton system (pH 2 to 10; total [Fe] = 3 mmol dm -3 ; total [citrate 3- ] 10 mmol dm -3 ) in which equilibrium constants have been determined using glass electrode potentiometry, speciation is predicted using the PHREEQE computer code, and validation of predictions is achieved by determination of iron complexation and redox state with associated concentrations. (authors)

Understanding Gulf War Illness: An Integrative Modeling Approach

Science.gov (United States)

2017-10-01

using a novel mathematical model. The computational biology approach will enable the consortium to quickly identify targets of dysfunction and find... computer / mathematical paradigms for evaluation of treatment strategies 12-30 50% Develop pilot clinical trials on basis of animal studies 24-36 60...the goal of testing chemical treatments. The immune and autonomic biomarkers will be tested using a computational modeling approach allowing for a

Numerical Validation of Chemical Compositional Model for Wettability Alteration Processes

Science.gov (United States)

Bekbauov, Bakhbergen; Berdyshev, Abdumauvlen; Baishemirov, Zharasbek; Bau, Domenico

2017-12-01

Chemical compositional simulation of enhanced oil recovery and surfactant enhanced aquifer remediation processes is a complex task that involves solving dozens of equations for all grid blocks representing a reservoir. In the present work, we perform a numerical validation of the newly developed mathematical formulation which satisfies the conservation laws of mass and energy and allows applying a sequential solution approach to solve the governing equations separately and implicitly. Through its application to the numerical experiment using a wettability alteration model and comparisons with existing chemical compositional model's numerical results, the new model has proven to be practical, reliable and stable.

A moni-modelling approach to manage groundwater risk to pesticide leaching at regional scale.

Science.gov (United States)

Di Guardo, Andrea; Finizio, Antonio

2016-03-01

Historically, the approach used to manage risk of chemical contamination of water bodies is based on the use of monitoring programmes, which provide a snapshot of the presence/absence of chemicals in water bodies. Monitoring is required in the current EU regulations, such as the Water Framework Directive (WFD), as a tool to record temporal variation in the chemical status of water bodies. More recently, a number of models have been developed and used to forecast chemical contamination of water bodies. These models combine information of chemical properties, their use, and environmental scenarios. Both approaches are useful for risk assessors in decision processes. However, in our opinion, both show flaws and strengths when taken alone. This paper proposes an integrated approach (moni-modelling approach) where monitoring data and modelling simulations work together in order to provide a common decision framework for the risk assessor. This approach would be very useful, particularly for the risk management of pesticides at a territorial level. It fulfils the requirement of the recent Sustainable Use of Pesticides Directive. In fact, the moni-modelling approach could be used to identify sensible areas where implement mitigation measures or limitation of use of pesticides, but even to effectively re-design future monitoring networks or to better calibrate the pedo-climatic input data for the environmental fate models. A case study is presented, where the moni-modelling approach is applied in Lombardy region (North of Italy) to identify groundwater vulnerable areas to pesticides. The approach has been applied to six active substances with different leaching behaviour, in order to highlight the advantages in using the proposed methodology. Copyright © 2015 Elsevier B.V. All rights reserved.

A review of operational, regional-scale, chemical weather forecasting models in Europe

Directory of Open Access Journals (Sweden)

J. Kukkonen

2012-01-01

Full Text Available Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research directions, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

Progress report on SYVAC chemical modelling studies during 1984/85

International Nuclear Information System (INIS)

Cross, J.E.; Read, D.; Smith, G.L.; Williams, D.R.

1985-05-01

This report summarises progress made from April 1984 to May 1985 on chemical modelling within the DOE SYVAC project. Three new computer programs; the reaction path codes, PHREEQE and EQ3/6, and the chemical transport simulator CHEMTRN, have been acquired. Their applicability, overall capabilities, ease of use and database requirements are assessed. Coupled approaches to geochemical - hydrological modelling and the use of CHEMTRN is discussed. Modelling has been performed in connection with the ''Dry Run Assessment''. Speciation and solubilities of the actinides were simulated, assuming the vault to be a concrete solution and the geosphere to be represented by Harwell site groundwater analyses. Model verification and validation by collaboration with experimentalists and other modellers is discussed. (author)

A fugacity approach for modeling the transport of airborne organic chemicals in an air/plant/soil system

International Nuclear Information System (INIS)

Oliver, L.D.; McKone, T.E.

1991-05-01

An important issue facing both public and private agencies is the identification and quantification of exposures by indirect pathways to toxic chemicals released to the atmosphere. With recent public concerns over pesticides such as malathion and alar in foods, greater attention is being given to the process of chemical uptake by plants. Whether chemicals taken up by plants can accumulate and ultimately enter the human food chain are important questions for determining health risks and safe levels of toxic air-pollutant emissions and pesticide application. A number of plant-toxicokinetic, or ''botanicokinetic,'' models have been developed to give estimates of how chemicals are partitioned and transported within plants. In this paper, we provide a brief review of these models, describing their main features and listing some of their advantages and disadvantages. We then describe and demonstrate a five-compartment air/plant/soil model, which builds on and extends the features included in previous models. We apply this model to the steady-state chemical partitioning of perchloroethylene, hexachlorobenzene, and 2,3,7,8-tetrachlorodibenzo-p-dioxin in grass as test cases. We conclude with a discussion of the advantages and limitations of the model

A Multi-scale, Multi-disciplinary Approach for Assessing the Technological, Economic, and Environmental Performance of Bio-based Chemicals

DEFF Research Database (Denmark)

Herrgard, Markus; Sukumara, Sumesh; Campodonico Alt, Miguel Angel

2015-01-01

, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain...... towards a sustainable chemical industry....

Quantum Chemical Approach to Estimating the Thermodynamics of Metabolic Reactions

OpenAIRE

Adrian Jinich; Dmitrij Rappoport; Ian Dunn; Benjamin Sanchez-Lengeling; Roberto Olivares-Amaya; Elad Noor; Arren Bar Even; Alán Aspuru-Guzik

2014-01-01

Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfe...

Micro-poromechanics model of fluid-saturated chemically active fibrous media.

Science.gov (United States)

Misra, Anil; Parthasarathy, Ranganathan; Singh, Viraj; Spencer, Paulette

2015-02-01

We have developed a micromechanics based model for chemically active saturated fibrous media that incorporates fiber network microstructure, chemical potential driven fluid flow, and micro-poromechanics. The stress-strain relationship of the dry fibrous media is first obtained by considering the fiber behavior. The constitutive relationships applicable to saturated media are then derived in the poromechanics framework using Hill's volume averaging. The advantage of this approach is that the resultant continuum model accounts for the discrete nature of the individual fibers while retaining a form suitable for porous materials. As a result, the model is able to predict the influence of micro-scale phenomena, such as the fiber pre-strain caused by osmotic effects and evolution of fiber network structure with loading, on the overall behavior and in particular, on the poromechanics parameters. Additionally, the model can describe fluid-flow related rate-dependent behavior under confined and unconfined conditions and varying chemical environments. The significance of the approach is demonstrated by simulating unconfined drained monotonic uniaxial compression under different surrounding fluid bath molarity, and fluid-flow related creep and relaxation at different loading-levels and different surrounding fluid bath molarity. The model predictions conform to the experimental observations for saturated soft fibrous materials. The method can potentially be extended to other porous materials such as bone, clays, foams and concrete.

Part 6: Modelling of simultaneous chemical-biological P removal ...

African Journals Online (AJOL)

drinie

approaches taken in modelling the chemical P removal processes. In the literature .... to 2 mgP/l) for an iron dose of ~1 to 10 mg/l as Fe - refer to dashed line in Fig. 1). ...... systems exhibiting biological enhanced phosphate removal. Part 3:.

Modeling turbulence structure. Chemical kinetics interaction in turbulent reactive flows

Energy Technology Data Exchange (ETDEWEB)

Magnussen, B F [The Norwegian Univ. of Science and Technology, Trondheim (Norway)

1998-12-31

The challenge of the mathematical modelling is to transfer basic physical knowledge into a mathematical formulation such that this knowledge can be utilized in computational simulation of practical problems. The combustion phenomena can be subdivided into a large set of interconnected phenomena like flow, turbulence, thermodynamics, chemical kinetics, radiation, extinction, ignition etc. Combustion in one application differs from combustion in another area by the relative importance of the various phenomena. The difference in fuel, geometry and operational conditions often causes the differences. The computer offers the opportunity to treat the individual phenomena and their interactions by models with wide operational domains. The relative magnitude of the various phenomena therefore becomes the consequence of operational conditions and geometry and need not to be specified on the basis of experience for the given problem. In mathematical modelling of turbulent combustion, one of the big challenges is how to treat the interaction between the chemical reactions and the fluid flow i.e. the turbulence. Different scientists adhere to different concepts like the laminar flamelet approach, the pdf approach of the Eddy Dissipation Concept. Each of these approaches offers different opportunities and problems. All these models are based on a sound physical basis, however none of these have general validity in taking into consideration all detail of the physical chemical interaction. The merits of the models can only be judged by their ability to reproduce physical reality and consequences of operational and geometric conditions in a combustion system. The presentation demonstrates and discusses the development of a coherent combustion technology for energy conversion and safety based on the Eddy Dissipation Concept by Magnussen. (author) 30 refs.

Modeling turbulence structure. Chemical kinetics interaction in turbulent reactive flows

Energy Technology Data Exchange (ETDEWEB)

Magnussen, B.F. [The Norwegian Univ. of Science and Technology, Trondheim (Norway)

1997-12-31

The challenge of the mathematical modelling is to transfer basic physical knowledge into a mathematical formulation such that this knowledge can be utilized in computational simulation of practical problems. The combustion phenomena can be subdivided into a large set of interconnected phenomena like flow, turbulence, thermodynamics, chemical kinetics, radiation, extinction, ignition etc. Combustion in one application differs from combustion in another area by the relative importance of the various phenomena. The difference in fuel, geometry and operational conditions often causes the differences. The computer offers the opportunity to treat the individual phenomena and their interactions by models with wide operational domains. The relative magnitude of the various phenomena therefore becomes the consequence of operational conditions and geometry and need not to be specified on the basis of experience for the given problem. In mathematical modelling of turbulent combustion, one of the big challenges is how to treat the interaction between the chemical reactions and the fluid flow i.e. the turbulence. Different scientists adhere to different concepts like the laminar flamelet approach, the pdf approach of the Eddy Dissipation Concept. Each of these approaches offers different opportunities and problems. All these models are based on a sound physical basis, however none of these have general validity in taking into consideration all detail of the physical chemical interaction. The merits of the models can only be judged by their ability to reproduce physical reality and consequences of operational and geometric conditions in a combustion system. The presentation demonstrates and discusses the development of a coherent combustion technology for energy conversion and safety based on the Eddy Dissipation Concept by Magnussen. (author) 30 refs.

A Conceptual Framework for Predicting the Toxicity of Reactive Chemicals: Modeling Soft Electrophilicity

Science.gov (United States)

Although the literature is replete with QSAR models developed for many toxic effects caused by reversible chemical interactions, the development of QSARs for the toxic effects of reactive chemicals lacks a consistent approach. While limitations exit, an appropriate starting-point...

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

Science.gov (United States)

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

Modeling food matrix effects on chemical reactivity: Challenges and perspectives.

Science.gov (United States)

Capuano, Edoardo; Oliviero, Teresa; van Boekel, Martinus A J S

2017-06-29

The same chemical reaction may be different in terms of its position of the equilibrium (i.e., thermodynamics) and its kinetics when studied in different foods. The diversity in the chemical composition of food and in its structural organization at macro-, meso-, and microscopic levels, that is, the food matrix, is responsible for this difference. In this viewpoint paper, the multiple, and interconnected ways the food matrix can affect chemical reactivity are summarized. Moreover, mechanistic and empirical approaches to explain and predict the effect of food matrix on chemical reactivity are described. Mechanistic models aim to quantify the effect of food matrix based on a detailed understanding of the chemical and physical phenomena occurring in food. Their applicability is limited at the moment to very simple food systems. Empirical modeling based on machine learning combined with data-mining techniques may represent an alternative, useful option to predict the effect of the food matrix on chemical reactivity and to identify chemical and physical properties to be further tested. In such a way the mechanistic understanding of the effect of the food matrix on chemical reactions can be improved.

Approach to chemical equilibrium in thermal models

International Nuclear Information System (INIS)

Boal, D.H.

1984-01-01

The experimentally measured (μ - , charged particle)/(μ - ,n) and (p,n/p,p') ratios for the emission of energetic nucleons are used to estimate the time evolution of a system of secondary nucleons produced in a direct interaction of a projectile or captured muon. The values of these ratios indicate that chemical equilibrium is not achieved among the secondary nucleons in noncomposite induced reactions, and this restricts the time scale for the emission of energetic nucleons to be about 0.7 x 10 -23 sec. It is shown that the reason why thermal equilibrium can be reached so rapidly for a particular nucleon species is that the sum of the particle spectra produced in multiple direct reactions looks surprisingly thermal. The rate equations used to estimate the reaction times for muon and nucleon induced reactions are then applied to heavy ion collisions, and it is shown that chemical equilibrium can be reached more rapidly, as one would expect

Engineering electrical properties of graphene: chemical approaches

International Nuclear Information System (INIS)

Kim, Yong-Jin; Kim, Yuna; Hong, Byung Hee; Novoselov, Konstantin

2015-01-01

To ensure the high performance of graphene-based devices, it is necessary to engineer the electrical properties of graphene with enhanced conductivity, controlled work function, opened or closed bandgaps, etc. This can be performed by various non-covalent chemical approaches, including molecular adsorption, substrate-induced doping, polymerization on graphene, deposition of metallic thin films or nanoparticles, etc. In addition, covalent approaches such as the substitution of carbon atoms with boron or nitrogen and the functionalization with hydrogen or fluorine are useful to tune the bandgaps more efficiently, with better uniformity and stability. In this review, representative examples of chemically engineered graphene and its device applications will be reviewed, and remaining challenges will be discussed. (topical review)

Mathematical model of phase transformations in thermo-chemical cathodes with zirconium insertion

International Nuclear Information System (INIS)

Kavokin, A.A.; Kazmi, I.H.

2007-01-01

The mathematical model of thermo-chemical processes in the cathode of plasmatron working in the gas environment is investigated. The model describes electromagnetic, temperature and concentration fields taking into account kinetic of phase transformation and chemical reaction in accordance with a state diagram. The offered approach is simpler than the Stefan's approach of describing an analogical phase transformation. As an example the case of copper cathodes with the zirconium insertion in the environment of oxygen is considered. The influence of separate parts of process on distribution of temperature inside of the insertion is estimated. On the basis of this analysis the opportunity of use of stationary approach for electric and temperature fields is shown and analytical formulas for temperature are received. After that a numerical solution for gas concentration distribution is obtained. The calculations on the specified model show that the size of area of a phase zirconium oxides depends mainly upon coefficient of diffusion of oxygen. The calculations for various types of dependencies of gas diffusion coefficient from temperature are concluded. The results of calculations develop understanding of some features of oxidation process of a zirconium insertion. Typical example of multi phase process model is the mathematical description of a heat and mass transfer occurring in metal which is being heated by an electric arch in the gas medium (1, 2, 4). The macroscopic model of physical and chemical transformations can be described as follows (3). As a metal is heated on the surface of an electrode as a function of rising results in the border dividing solid and liquid phases moves ahead deep into the electrode. At the same time there is a diffusion of gas in electrode and formation of new chemical compounds which can noticeably differ in the physical and chemical properties from each other and metal of the electrode. Moreover we shall name a phase of substance not

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

Science.gov (United States)

Willis, Matthew P.; Stevenson, Shawn M.; Pearl, Thomas P.; Mantooth, Brent A.

2014-01-01

The ability to directly characterize chemical transport and interactions that occur within a material (i.e., subsurface dynamics) is a vital component in understanding contaminant mass transport and the ability to decontaminate materials. If a material is contaminated, over time, the transport of highly toxic chemicals (such as chemical warfare agent species) out of the material can result in vapor exposure or transfer to the skin, which can result in percutaneous exposure to personnel who interact with the material. Due to the high toxicity of chemical warfare agents, the release of trace chemical quantities is of significant concern. Mapping subsurface concentration distribution and transport characteristics of absorbed agents enables exposure hazards to be assessed in untested conditions. Furthermore, these tools can be used to characterize subsurface reaction dynamics to ultimately design improved decontaminants or decontamination procedures. To achieve this goal, an inverse analysis mass transport modeling approach was developed that utilizes time-resolved mass spectroscopy measurements of vapor emission from contaminated paint coatings as the input parameter for calculation of subsurface concentration profiles. Details are provided on sample preparation, including contaminant and material handling, the application of mass spectrometry for the measurement of emitted contaminant vapor, and the implementation of inverse analysis using a physics-based diffusion model to determine transport properties of live chemical warfare agents including distilled mustard (HD) and the nerve agent VX. PMID:25226346

A review of models for near-field exposure pathways of chemicals in consumer products

DEFF Research Database (Denmark)

Huang, Lei; Ernstoff, Alexi; Fantke, Peter

2017-01-01

able to quantify the multiple transfers of chemicals from products used near-field to humans. The present review therefore aims at an in-depth overview of modeling approaches for near-field chemical release and human exposure pathways associated with consumer products. It focuses on lower......-tier, mechanistic models suitable for life cycle assessments (LCA), chemical alternative assessment (CAA) and high-throughput screening risk assessment (HTS). Chemicals in a product enter the near-field via a defined “compartment of entry”, are transformed or transferred to adjacent compartments, and eventually end......Exposure to chemicals in consumer products has been gaining increasing attention, with multiple studies showing that near-field exposures from products is high compared to far-field exposures. Regarding the numerous chemical-product combinations, there is a need for an overarching review of models...

High-throughput migration modelling for estimating exposure to chemicals in food packaging in screening and prioritization tools

DEFF Research Database (Denmark)

Ernstoff, Alexi S; Fantke, Peter; Huang, Lei

2017-01-01

Specialty software and simplified models are often used to estimate migration of potentially toxic chemicals from packaging into food. Current models, however, are not suitable for emerging applications in decision-support tools, e.g. in Life Cycle Assessment and risk-based screening and prioriti...... to uncertainty and dramatically decreased model performance (R2 = 0.4, Se = 1). In all, this study provides a rapid migration modelling approach to estimate exposure to chemicals in food packaging for emerging screening and prioritization approaches....

A generalised chemical precipitation modelling approach in wastewater treatment applied to calcite

DEFF Research Database (Denmark)

Mbamba, Christian Kazadi; Batstone, Damien J.; Flores Alsina, Xavier

2015-01-01

, the present study aims to identify a broadly applicable precipitation modelling approach. The study uses two experimental platforms applied to calcite precipitating from synthetic aqueous solutions to identify and validate the model approach. Firstly, dynamic pH titration tests are performed to define...... an Arrhenius-style correction of kcryst. The influence of magnesium (a common and representative added impurity) on kcryst was found to be significant but was considered an optional correction because of a lesser influence as compared to that of temperature. Other variables such as ionic strength and pH were...

A systems engineering approach to manage the complexity in sustainable chemical product-process design

DEFF Research Database (Denmark)

Gani, Rafiqul

This paper provides a perspective on model-data based solution approaches for chemical product-process design, which consists of finding the identity of the candidate chemical product, designing the process that can sustainably manufacture it and verifying the performance of the product during...... framework can manage the complexity associated with product-process problems very efficiently. Three specific computer-aided tools (ICAS, Sustain-Pro and VPPDLab) have been presented and their applications to product-process design, highlighted....

Review on chemical processes around the facilities in deep underground and study on numerical approach to evaluate them

International Nuclear Information System (INIS)

Sawada, Masataka

2003-01-01

The facilities for radioactive waste repositories are constructed in deep underground. Various chemical reactions including microbial activities may affect the long-term performance of the barrier system. An advancement of the evaluation method for the long-term behavior of barrier materials is desired. One of the efficient approaches is numerical simulation based on modeling of chemical processes. In the first part of this report, chemical processes and microbial reactions that can affect the performance of facilities in deep underground are reviewed. For example, dissolution and precipitation of minerals composing bentonite and rock are caused by highly alkaline water from cementitious materials. Numerical approaches to the chemical processes are also studied. Most chemical processes are reactions between groundwater (or solutes in it) and minerals composing barrier materials. So they can be simulated by coupled reaction rate transport analyses. Some analysis codes are developed and applied to problems in radioactive waste disposal. Microbial reaction rate can be modeled using the growth equation of microorganisms. In order to evaluate the performance of the barrier system after altered by chemical processes, not only the change in composition but also properties of altered materials is required to be obtained as output of numerical simulation. If the relationships between reaction rate and material properties are obtained, time history and spatial distribution of material properties can also be obtained by the coupled reaction rate transport analysis. At present, modeling study on the relationships between them is not sufficient, and obtaining such relationships using both theoretical and experimental approaches are also an important research target. (author)

The TSCA interagency testing committee`s approaches to screening and scoring chemicals and chemical groups: 1977-1983

Energy Technology Data Exchange (ETDEWEB)

Walker, J.D. [Environmental Protection Agency, Washington, DC (United States)

1990-12-31

This paper describes the TSCA interagency testing committee`s (ITC) approaches to screening and scoring chemicals and chemical groups between 1977 and 1983. During this time the ITC conducted five scoring exercises to select chemicals and chemical groups for detailed review and to determine which of these chemicals and chemical groups should be added to the TSCA Section 4(e) Priority Testing List. 29 refs., 1 fig., 2 tabs.

Chemical reactor modeling multiphase reactive flows

CERN Document Server

Jakobsen, Hugo A

2014-01-01

Chemical Reactor Modeling closes the gap between Chemical Reaction Engineering and Fluid Mechanics.  The second edition consists of two volumes: Volume 1: Fundamentals. Volume 2: Chemical Engineering Applications In volume 1 most of the fundamental theory is presented. A few numerical model simulation application examples are given to elucidate the link between theory and applications. In volume 2 the chemical reactor equipment to be modeled are described. Several engineering models are introduced and discussed. A survey of the frequently used numerical methods, algorithms and schemes is provided. A few practical engineering applications of the modeling tools are presented and discussed. The working principles of several experimental techniques employed in order to get data for model validation are outlined. The monograph is based on lectures regularly taught in the fourth and fifth years graduate courses in transport phenomena and chemical reactor modeling, and in a post graduate course in modern reactor m...

Bayesian inference of chemical kinetic models from proposed reactions

KAUST Repository

Galagali, Nikhil

2015-02-01

© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model structure. Most existing applications of Bayesian model selection methods to chemical kinetics have been limited to comparisons among a small set of models, however. The significant computational cost of evaluating posterior model probabilities renders traditional Bayesian methods infeasible when the model space becomes large. We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. The posterior samples are used to identify plausible models, to quantify rate constant uncertainties, and to extract key diagnostic information about model structure-such as the reactions and operating pathways most strongly supported by the data. We provide numerical demonstrations of the proposed framework by inferring kinetic models for catalytic steam and dry reforming of methane using available experimental data.

Exploring the Use of Multiple Analogical Models when Teaching and Learning Chemical Equilibrium

Science.gov (United States)

Harrison, Allan G.; De Jong, Onno

2005-01-01

This study describes the multiple analogical models used to introduce and teach Grade 12 chemical equilibrium. We examine the teacher's reasons for using models, explain each model's development during the lessons, and analyze the understandings students derived from the models. A case study approach was used and the data were drawn from the…

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems

Science.gov (United States)

Winkelmann, Stefanie; Schütte, Christof

2017-09-01

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

Hybrid models for chemical reaction networks: Multiscale theory and application to gene regulatory systems.

Science.gov (United States)

Winkelmann, Stefanie; Schütte, Christof

2017-09-21

Well-mixed stochastic chemical kinetics are properly modeled by the chemical master equation (CME) and associated Markov jump processes in molecule number space. If the reactants are present in large amounts, however, corresponding simulations of the stochastic dynamics become computationally expensive and model reductions are demanded. The classical model reduction approach uniformly rescales the overall dynamics to obtain deterministic systems characterized by ordinary differential equations, the well-known mass action reaction rate equations. For systems with multiple scales, there exist hybrid approaches that keep parts of the system discrete while another part is approximated either using Langevin dynamics or deterministically. This paper aims at giving a coherent overview of the different hybrid approaches, focusing on their basic concepts and the relation between them. We derive a novel general description of such hybrid models that allows expressing various forms by one type of equation. We also check in how far the approaches apply to model extensions of the CME for dynamics which do not comply with the central well-mixed condition and require some spatial resolution. A simple but meaningful gene expression system with negative self-regulation is analysed to illustrate the different approximation qualities of some of the hybrid approaches discussed. Especially, we reveal the cause of error in the case of small volume approximations.

A probabilistic approach for validating protein NMR chemical shift assignments

International Nuclear Information System (INIS)

Wang Bowei; Wang, Yunjun; Wishart, David S.

2010-01-01

It has been estimated that more than 20% of the proteins in the BMRB are improperly referenced and that about 1% of all chemical shift assignments are mis-assigned. These statistics also reflect the likelihood that any newly assigned protein will have shift assignment or shift referencing errors. The relatively high frequency of these errors continues to be a concern for the biomolecular NMR community. While several programs do exist to detect and/or correct chemical shift mis-referencing or chemical shift mis-assignments, most can only do one, or the other. The one program (SHIFTCOR) that is capable of handling both chemical shift mis-referencing and mis-assignments, requires the 3D structure coordinates of the target protein. Given that chemical shift mis-assignments and chemical shift re-referencing issues should ideally be addressed prior to 3D structure determination, there is a clear need to develop a structure-independent approach. Here, we present a new structure-independent protocol, which is based on using residue-specific and secondary structure-specific chemical shift distributions calculated over small (3-6 residue) fragments to identify mis-assigned resonances. The method is also able to identify and re-reference mis-referenced chemical shift assignments. Comparisons against existing re-referencing or mis-assignment detection programs show that the method is as good or superior to existing approaches. The protocol described here has been implemented into a freely available Java program called 'Probabilistic Approach for protein Nmr Assignment Validation (PANAV)' and as a web server (http://redpoll.pharmacy.ualberta.ca/PANAVhttp://redpoll.pharmacy.ualberta.ca/PANAV) which can be used to validate and/or correct as well as re-reference assigned protein chemical shifts.

A Comprehensive Approach for Pectin Chemical and Functional Characterization

DEFF Research Database (Denmark)

de Sousa, António Felipe Gomes Teixeira

In this work, a comprehensive approach for the chemical and functional analysis of pectin was used in order to relate the different extraction conditions used to the polymer structure and the final functional (mainly gelling) properties. A wide range of methods were utilized including chemical an...

A model for chemically-induced mechanical loading on MEMS

DEFF Research Database (Denmark)

Amiot, Fabien

2007-01-01

The development of full displacement field measurements as an alternative to the optical lever technique to measure the mechanical response for microelectro-mechanical systems components in their environment calls for a modeling of chemically-induced mechanical fields (stress, strain, and displac......The development of full displacement field measurements as an alternative to the optical lever technique to measure the mechanical response for microelectro-mechanical systems components in their environment calls for a modeling of chemically-induced mechanical fields (stress, strain...... of the system free energy and its dependence on the surface amount. It is solved in the cantilever case thanks to an asymptotic analysis, and an approached closed-form solution is obtained for the interfacial stress field. Finally, some conclusions regarding the transducer efficiency of cantilevers are drawn...

Endocrine disrupting chemicals in fish: developing exposure indicators and predictive models of effects based on mechanism of action.

Science.gov (United States)

Ankley, Gerald T; Bencic, David C; Breen, Michael S; Collette, Timothy W; Conolly, Rory B; Denslow, Nancy D; Edwards, Stephen W; Ekman, Drew R; Garcia-Reyero, Natalia; Jensen, Kathleen M; Lazorchak, James M; Martinović, Dalma; Miller, David H; Perkins, Edward J; Orlando, Edward F; Villeneuve, Daniel L; Wang, Rong-Lin; Watanabe, Karen H

2009-05-05

Knowledge of possible toxic mechanisms (or modes) of action (MOA) of chemicals can provide valuable insights as to appropriate methods for assessing exposure and effects, thereby reducing uncertainties related to extrapolation across species, endpoints and chemical structure. However, MOA-based testing seldom has been used for assessing the ecological risk of chemicals. This is in part because past regulatory mandates have focused more on adverse effects of chemicals (reductions in survival, growth or reproduction) than the pathways through which these effects are elicited. A recent departure from this involves endocrine-disrupting chemicals (EDCs), where there is a need to understand both MOA and adverse outcomes. To achieve this understanding, advances in predictive approaches are required whereby mechanistic changes caused by chemicals at the molecular level can be translated into apical responses meaningful to ecological risk assessment. In this paper we provide an overview and illustrative results from a large, integrated project that assesses the effects of EDCs on two small fish models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio). For this work a systems-based approach is being used to delineate toxicity pathways for 12 model EDCs with different known or hypothesized toxic MOA. The studies employ a combination of state-of-the-art genomic (transcriptomic, proteomic, metabolomic), bioinformatic and modeling approaches, in conjunction with whole animal testing, to develop response linkages across biological levels of organization. This understanding forms the basis for predictive approaches for species, endpoint and chemical extrapolation. Although our project is focused specifically on EDCs in fish, we believe that the basic conceptual approach has utility for systematically assessing exposure and effects of chemicals with other MOA across a variety of biological systems.

A novel approach to modeling and diagnosing the cardiovascular system

Energy Technology Data Exchange (ETDEWEB)

Keller, P.E.; Kangas, L.J.; Hashem, S.; Kouzes, R.T. [Pacific Northwest Lab., Richland, WA (United States); Allen, P.A. [Life Link, Richland, WA (United States)

1995-07-01

A novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.

An extended risk assessment approach for chemical plants applied to a study related to pipe ruptures

International Nuclear Information System (INIS)

Milazzo, Maria Francesca; Aven, Terje

2012-01-01

Risk assessments and Quantitative Risk Assessment (QRA) in particular have been used in the chemical industry for many years to support decision-making on the choice of arrangements and measures associated with chemical processes, transportation and storage of dangerous substances. The assessments have been founded on a risk perspective seeing risk as a function of frequency of events (probability) and associated consequences. In this paper we point to the need for extending this approach to place a stronger emphasis on uncertainties. A recently developed risk framework designed to better reflect such uncertainties is presented and applied to a chemical plant and specifically the analysis of accidental events related to the rupture of pipes. Two different ways of implementing the framework are presented, one based on the introduction of probability models and one without. The differences between the standard approach and the extended approaches are discussed from a theoretical point of view as well as from a practical risk analyst perspective.

Modelling Dietary Exposure to Chemical Components in Heat-Processed Meats

DEFF Research Database (Denmark)

Georgiadis, Stylianos; Jakobsen, Lea Sletting; Nielsen, Bo Friis

Several chemical compounds that potentially increase the risk of developing cancer in humans are formed during heat processing of meat. Estimating the overall health impact of these compounds in the population requires accurate estimation of the exposure to the chemicals, as well as the probabili.......g. the Poisson-Lognormal approach, are promising tools to address this obstacle. The exposure estimates can then be applied to dose-response models to quantify the cancer risk.......Several chemical compounds that potentially increase the risk of developing cancer in humans are formed during heat processing of meat. Estimating the overall health impact of these compounds in the population requires accurate estimation of the exposure to the chemicals, as well as the probability...... that different levels of exposure result in disease. The overall goal of this study was to evaluate the impact of variability of exposure patterns and uncertainty of exposure data in burden of disease estimates. We focus on the first phase of burden of disease modelling, i.e. the estimation of exposure...

Chempy: A flexible chemical evolution model for abundance fitting. Do the Sun's abundances alone constrain chemical evolution models?

Science.gov (United States)

Rybizki, Jan; Just, Andreas; Rix, Hans-Walter

2017-09-01

Elemental abundances of stars are the result of the complex enrichment history of their galaxy. Interpretation of observed abundances requires flexible modeling tools to explore and quantify the information about Galactic chemical evolution (GCE) stored in such data. Here we present Chempy, a newly developed code for GCE modeling, representing a parametrized open one-zone model within a Bayesian framework. A Chempy model is specified by a set of five to ten parameters that describe the effective galaxy evolution along with the stellar and star-formation physics: for example, the star-formation history (SFH), the feedback efficiency, the stellar initial mass function (IMF), and the incidence of supernova of type Ia (SN Ia). Unlike established approaches, Chempy can sample the posterior probability distribution in the full model parameter space and test data-model matches for different nucleosynthetic yield sets. It is essentially a chemical evolution fitting tool. We straightforwardly extend Chempy to a multi-zone scheme. As an illustrative application, we show that interesting parameter constraints result from only the ages and elemental abundances of the Sun, Arcturus, and the present-day interstellar medium (ISM). For the first time, we use such information to infer the IMF parameter via GCE modeling, where we properly marginalize over nuisance parameters and account for different yield sets. We find that 11.6+ 2.1-1.6% of the IMF explodes as core-collapse supernova (CC-SN), compatible with Salpeter (1955, ApJ, 121, 161). We also constrain the incidence of SN Ia per 103M⊙ to 0.5-1.4. At the same time, this Chempy application shows persistent discrepancies between predicted and observed abundances for some elements, irrespective of the chosen yield set. These cannot be remedied by any variations of Chempy's parameters and could be an indication of missing nucleosynthetic channels. Chempy could be a powerful tool to confront predictions from stellar

Chemical Graph Transformation with Stereo-Information

DEFF Research Database (Denmark)

Andersen, Jakob Lykke; Flamm, Christoph; Merkle, Daniel

2017-01-01

Double Pushout graph transformation naturally facilitates the modelling of chemical reactions: labelled undirected graphs model molecules and direct derivations model chemical reactions. However, the most straightforward modelling approach ignores the relative placement of atoms and their neighbo......Double Pushout graph transformation naturally facilitates the modelling of chemical reactions: labelled undirected graphs model molecules and direct derivations model chemical reactions. However, the most straightforward modelling approach ignores the relative placement of atoms...... and their neighbours in space. Stereoisomers of chemical compounds thus cannot be distinguished, even though their chemical activity may differ substantially. In this contribution we propose an extended chemical graph transformation system with attributes that encode information about local geometry. The modelling...... of graph transformation, but we here propose a framework that also allows for partially specified stereoinformation. While there are several stereochemical configurations to be considered, we focus here on the tetrahedral molecular shape, and suggest general principles for how to treat all other chemically...

High-throughput migration modelling for estimating exposure to chemicals in food packaging in screening and prioritization tools.

Science.gov (United States)

Ernstoff, Alexi S; Fantke, Peter; Huang, Lei; Jolliet, Olivier

2017-11-01

Specialty software and simplified models are often used to estimate migration of potentially toxic chemicals from packaging into food. Current models, however, are not suitable for emerging applications in decision-support tools, e.g. in Life Cycle Assessment and risk-based screening and prioritization, which require rapid computation of accurate estimates for diverse scenarios. To fulfil this need, we develop an accurate and rapid (high-throughput) model that estimates the fraction of organic chemicals migrating from polymeric packaging materials into foods. Several hundred step-wise simulations optimised the model coefficients to cover a range of user-defined scenarios (e.g. temperature). The developed model, operationalised in a spreadsheet for future dissemination, nearly instantaneously estimates chemical migration, and has improved performance over commonly used model simplifications. When using measured diffusion coefficients the model accurately predicted (R 2  = 0.9, standard error (S e ) = 0.5) hundreds of empirical data points for various scenarios. Diffusion coefficient modelling, which determines the speed of chemical transfer from package to food, was a major contributor to uncertainty and dramatically decreased model performance (R 2  = 0.4, S e  = 1). In all, this study provides a rapid migration modelling approach to estimate exposure to chemicals in food packaging for emerging screening and prioritization approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

NIF: Impacts of chemical accidents and comparison of chemical/radiological accident approaches

International Nuclear Information System (INIS)

Lazaro, M.A.; Policastro, A.J.; Rhodes, M.

1996-01-01

The US Department of Energy (DOE) proposes to construct and operate the National Ignition Facility (NIF). The goals of the NIF are to (1) achieve fusion ignition in the laboratory for the first time by using inertial confinement fusion (ICF) technology based on an advanced-design neodymium glass solid-state laser, and (2) conduct high-energy-density experiments in support of national security and civilian applications. The primary focus of this paper is worker-public health and safety issues associated with postulated chemical accidents during the operation of NIF. The key findings from the accident analysis will be presented. Although NIF chemical accidents will be emphasized, the important differences between chemical and radiological accident analysis approaches and the metrics for reporting results will be highlighted. These differences are common EIS facility and transportation accident assessments

Modeling of turbulent chemical reaction

Science.gov (United States)

Chen, J.-Y.

1995-01-01

Viewgraphs are presented on modeling turbulent reacting flows, regimes of turbulent combustion, regimes of premixed and regimes of non-premixed turbulent combustion, chemical closure models, flamelet model, conditional moment closure (CMC), NO(x) emissions from turbulent H2 jet flames, probability density function (PDF), departures from chemical equilibrium, mixing models for PDF methods, comparison of predicted and measured H2O mass fractions in turbulent nonpremixed jet flames, experimental evidence of preferential diffusion in turbulent jet flames, and computation of turbulent reacting flows.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

Science.gov (United States)

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

A New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish.

Directory of Open Access Journals (Sweden)

Guozhu Zhang

Full Text Available Zebrafish have become an important alternative model for characterizing chemical bioactivity, partly due to the efficiency at which systematic, high-dimensional data can be generated. However, these new data present analytical challenges associated with scale and diversity. We developed a novel, robust statistical approach to characterize chemical-elicited effects in behavioral data from high-throughput screening (HTS of all 1,060 Toxicity Forecaster (ToxCast™ chemicals across 5 concentrations at 120 hours post-fertilization (hpf. Taking advantage of the immense scale of data for a global view, we show that this new approach reduces bias introduced by extreme values yet allows for diverse response patterns that confound the application of traditional statistics. We have also shown that, as a summary measure of response for local tests of chemical-associated behavioral effects, it achieves a significant reduction in coefficient of variation compared to many traditional statistical modeling methods. This effective increase in signal-to-noise ratio augments statistical power and is observed across experimental periods (light/dark conditions that display varied distributional response patterns. Finally, we integrated results with data from concomitant developmental endpoint measurements to show that appropriate statistical handling of HTS behavioral data can add important biological context that informs mechanistic hypotheses.

Graphene: chemical approaches to the synthesis and modification

Energy Technology Data Exchange (ETDEWEB)

Grayfer, E D; Makotchenko, V G; Nazarov, Albert S; Kim, S J; Fedorov, Vladimir E

2011-08-31

Published data on the new carbon nanomaterial, graphene, are described systematically from the chemist's standpoint. The attention is focused on the chemical methods of the synthesis of graphene-like materials from various precursors: natural and expanded graphite, graphite oxide, graphite intercalation compounds, etc. Approaches to the chemical modification of the graphene plane by various reagents and routes for the preparation of colloidal dispersions of graphene are considered. The bibliography includes 220 references.

Modeling heat dissipation at the nanoscale: an embedding approach for chemical reaction dynamics on metal surfaces.

Science.gov (United States)

Meyer, Jörg; Reuter, Karsten

2014-04-25

We present an embedding technique for metallic systems that makes it possible to model energy dissipation into substrate phonons during surface chemical reactions from first principles. The separation of chemical and elastic contributions to the interaction potential provides a quantitative description of both electronic and phononic band structure. Application to the dissociation of O2 at Pd(100) predicts translationally "hot" oxygen adsorbates as a consequence of the released adsorption energy (ca. 2.6 eV). This finding questions the instant thermalization of reaction enthalpies generally assumed in models of heterogeneous catalysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Heat transfer modeling an inductive approach

CERN Document Server

Sidebotham, George

2015-01-01

This innovative text emphasizes a "less-is-more" approach to modeling complicated systems such as heat transfer by treating them first as "1-node lumped models" that yield simple closed-form solutions. The author develops numerical techniques for students to obtain more detail, but also trains them to use the techniques only when simpler approaches fail. Covering all essential methods offered in traditional texts, but with a different order, Professor Sidebotham stresses inductive thinking and problem solving as well as a constructive understanding of modern, computer-based practice. Readers learn to develop their own code in the context of the material, rather than just how to use packaged software, offering a deeper, intrinsic grasp behind models of heat transfer. Developed from over twenty-five years of lecture notes to teach students of mechanical and chemical engineering at The Cooper Union for the Advancement of Science and Art, the book is ideal for students and practitioners across engineering discipl...

Non-equilibrium Quasi-Chemical Nucleation Model

Science.gov (United States)

Gorbachev, Yuriy E.

2018-04-01

Quasi-chemical model, which is widely used for nucleation description, is revised on the basis of recent results in studying of non-equilibrium effects in reacting gas mixtures (Kolesnichenko and Gorbachev in Appl Math Model 34:3778-3790, 2010; Shock Waves 23:635-648, 2013; Shock Waves 27:333-374, 2017). Non-equilibrium effects in chemical reactions are caused by the chemical reactions themselves and therefore these contributions should be taken into account in the corresponding expressions for reaction rates. Corrections to quasi-equilibrium reaction rates are of two types: (a) spatially homogeneous (caused by physical-chemical processes) and (b) spatially inhomogeneous (caused by gas expansion/compression processes and proportional to the velocity divergency). Both of these processes play an important role during the nucleation and are included into the proposed model. The method developed for solving the generalized Boltzmann equation for chemically reactive gases is applied for solving the set of equations of the revised quasi-chemical model. It is shown that non-equilibrium processes lead to essential deviation of the quasi-stationary distribution and therefore the nucleation rate from its traditional form.

Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis.

Science.gov (United States)

Zhu, Hao; Tropsha, Alexander; Fourches, Denis; Varnek, Alexandre; Papa, Ester; Gramatica, Paola; Oberg, Tomas; Dao, Phuong; Cherkasov, Artem; Tetko, Igor V

2008-04-01

Selecting most rigorous quantitative structure-activity relationship (QSAR) approaches is of great importance in the development of robust and predictive models of chemical toxicity. To address this issue in a systematic way, we have formed an international virtual collaboratory consisting of six independent groups with shared interests in computational chemical toxicology. We have compiled an aqueous toxicity data set containing 983 unique compounds tested in the same laboratory over a decade against Tetrahymena pyriformis. A modeling set including 644 compounds was selected randomly from the original set and distributed to all groups that used their own QSAR tools for model development. The remaining 339 compounds in the original set (external set I) as well as 110 additional compounds (external set II) published recently by the same laboratory (after this computational study was already in progress) were used as two independent validation sets to assess the external predictive power of individual models. In total, our virtual collaboratory has developed 15 different types of QSAR models of aquatic toxicity for the training set. The internal prediction accuracy for the modeling set ranged from 0.76 to 0.93 as measured by the leave-one-out cross-validation correlation coefficient ( Q abs2). The prediction accuracy for the external validation sets I and II ranged from 0.71 to 0.85 (linear regression coefficient R absI2) and from 0.38 to 0.83 (linear regression coefficient R absII2), respectively. The use of an applicability domain threshold implemented in most models generally improved the external prediction accuracy but at the same time led to a decrease in chemical space coverage. Finally, several consensus models were developed by averaging the predicted aquatic toxicity for every compound using all 15 models, with or without taking into account their respective applicability domains. We find that consensus models afford higher prediction accuracy for the

Chemical toxicity approach for emergency response

International Nuclear Information System (INIS)

Bauer, T.

2009-01-01

In the event of an airborne release of chemical agent or toxic industrial chemical by accidental or intentional means, emergency responders must have a reasonable estimate of the location and size of the resulting hazard area. Emergency responders are responsible for warning persons downwind of the hazard to evacuate or shelter-in-place and must know where to look for casualties after the hazard has passed or dissipated. Given the same source characterization, modern hazard assessment models provide comparable concentration versus location and time estimates. Even urban hazard assessment models often provide similar predictions. There is a major shortcoming, though, in applying model output to estimating human toxicity effects. There exist a variety of toxicity values for non-lethal effects ranging from short-term to occupational to lifetime exposures. For health and safety purposes, these estimates are all safe-sided in converting animal data to human effects and in addressing the most sensitive subset of the population. In addition, these values are usually based on an assumed 1 hour exposure duration at constant concentration and do not reflect either a passing clouds concentration profile or duration. Emergency responders need expected value toxicity parameters rather than the existing safe-sided ones. This presentation will specify the types of toxicity values needed to provide appropriate chemical hazard estimates to emergency responders and will demonstrate how dramatically their use changes the hazard area.(author)

An approach to fabricating chemical sensors based on ZnO nanorod arrays

International Nuclear Information System (INIS)

Park, Jae Young; Song, Dong Eon; Kim, Sang Sub

2008-01-01

Vertically and laterally aligned ZnO nanorod arrays were synthesized on Pt-coated Si substrates by catalyst-free metal organic chemical vapor deposition. An approach to fabricating chemical sensors based on the nanorod arrays using a coating-and-etching process with a photo-resist is reported. Tests of the devices as oxygen gas sensors have been performed. Our results demonstrate that the approach holds promise for the realization of sensitive and reliable nanorod array chemical sensors

A computational approach to chemical etiologies of diabetes

DEFF Research Database (Denmark)

Audouze, Karine Marie Laure; Brunak, Søren; Grandjean, Philippe

2013-01-01

Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic...... linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene...

Progress report on SYVAC chemical speciation modelling studies during 1983/4

International Nuclear Information System (INIS)

Cross, J.; Smith, G.L.; Williams, D.R.

1984-01-01

This report summarises progress made on the SYVAC (System Variability Analysis program) chemical speciation project during 1983-4. Chemical speciation is defined and its importance in the SYVAC approach to Radioactive Waste Management is discussed. Computer modelling of chemical equilibria is described and the two programs presently operational at UWIST - SOLMNQ and MINEQL - are compared and discussed in detail. In view of the shortcomings of the databases supplied with these programs, a new database of equilibrium constants has been compiled containing 483 aqueous species and 329 solid phases, including data for the radionuclides uranium, plutonium, americium, neptunium and thorium. The collaborative work with AERE, Harwell, is reported. A leaching experiment carried out at Harwell has been modelled using the chemical speciation programs. The results for uranium, plutonium, americium and neptunium, are presented. However, the experimental data provided by AERE is insufficient for accurate simulations. Chemical speciation studies relating to specific sites require accurate characterisation of the groundwater, i.e. chemical composition, Eh and pH. In the absence of such information, preliminary studies have been made using an average granite groundwater. The results of these studies are presented and include solubility and speciation plots for uranium, plutonium, thorium and neptunium. The future aims of the project are discussed. (author)

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

Science.gov (United States)

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

A new generic approach for estimating the concentrations of down-the-drain chemicals at catchment and national scale

Energy Technology Data Exchange (ETDEWEB)

Keller, V.D.J. [Centre for Ecology and Hydrology, Hydrological Risks and Resources, Maclean Building, Crowmarsh Gifford, Wallingford OX10 8BB (United Kingdom)]. E-mail: vke@ceh.ac.uk; Rees, H.G. [Centre for Ecology and Hydrology, Hydrological Risks and Resources, Maclean Building, Crowmarsh Gifford, Wallingford OX10 8BB (United Kingdom); Fox, K.K. [University of Lancaster (United Kingdom); Whelan, M.J. [Unilever Safety and Environmental Assurance Centre, Colworth (United Kingdom)

2007-07-15

A new generic approach for estimating chemical concentrations in rivers at catchment and national scales is presented. Domestic chemical loads in waste water are estimated using gridded population data. River flows are estimated by combining predicted runoff with topographically derived flow direction. Regional scale exposure is characterised by two summary statistics: PEC{sub works}, the average concentration immediately downstream of emission points, and, PEC{sub area}, the catchment-average chemical concentration. The method was applied to boron at national (England and Wales) and catchment (Aire-Calder) scales. Predicted concentrations were within 50% of measured mean values in the Aire-Calder catchment and in agreement with results from the GREAT-ER model. The concentration grids generated provide a picture of the spatial distribution of expected chemical concentrations at various scales, and can be used to identify areas of potentially high risk. - A new grid-based approach to predict spatially-referenced freshwater concentrations of domestic chemicals.

Modelling chemical behavior of water reactor fuel

Energy Technology Data Exchange (ETDEWEB)

Ball, R G.J.; Hanshaw, J; Mason, P K; Mignanelli, M A [AEA Technology, Harwell (United Kingdom)

1997-08-01

For many applications, large computer codes have been developed which use correlation`s, simplifications and approximations in order to describe the complex situations which may occur during the operation of nuclear power plant or during fault scenarios. However, it is important to have a firm physical basis for simplifications and approximations in such codes and, therefore, there has been an emphasis on modelling the behaviour of materials and processes on a more detailed or fundamental basis. The application of fundamental modelling techniques to simulated various chemical phenomena in thermal reactor fuel systems are described in this paper. These methods include thermochemical modelling, kinetic and mass transfer modelling and atomistic simulation and examples of each approach are presented. In each of these applications a summary of the methods are discussed together with the assessment process adopted to provide the fundamental parameters which form the basis of the calculation. (author). 25 refs, 9 figs, 2 tabs.

The next generation of galaxy evolution models: A symbiosis of stellar populations and chemical abundances

Science.gov (United States)

Kotulla, Ralf

2012-10-01

Over its lifespan Hubble has invested significant effort into detailed observations of galaxies both in the local and distant universe. To extract the physical information from the observed {spectro-}photometry requires detailed and accurate models. Stellar population synthesis models are frequently used to obtain stellar masses, star formation rate, galaxy ages and star formation histories. Chemical evolution models offer another valuable and complementary approach to gain insight into many of the same aspects, yet these two methods have rarely been used in combination.Our proposed next generation of galaxy evolution models will help us improve our understanding of how galaxies form and evolve. Building on GALEV evolutionary synthesis models we incorporate state-of-the-art input physics for stellar evolution of binaries and rotating stars as well as new spectral libraries well matched to the modern observational capabilities. Our improved chemical evolution model allows us to self-consistently trace abundances of individual elements, fully accounting for the increasing initial abundances of successive stellar generations. GALEV will support variable Initial Mass Functions {IMF}, enabling us to test recent observational findings of a non-universal IMF by predicting chemical properties and integrated spectra in an integrated and consistent manner.HST is the perfect instrument for testing this approach. Its wide wavelength coverage from UV to NIR enables precise SED fitting, and with its spatial resolution we can compare the inferred chemical evolution to studies of star clusters and resolved stellar populations in nearby galaxies.

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

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B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ2 and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

Directory of Open Access Journals (Sweden)

B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ² and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Modeling lightning-NOx chemistry on a sub-grid scale in a global chemical transport model

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A. Gressent

2016-05-01

Full Text Available For the first time, a plume-in-grid approach is implemented in a chemical transport model (CTM to parameterize the effects of the nonlinear reactions occurring within high concentrated NOx plumes from lightning NOx emissions (LNOx in the upper troposphere. It is characterized by a set of parameters including the plume lifetime, the effective reaction rate constant related to NOx–O3 chemical interactions, and the fractions of NOx conversion into HNO3 within the plume. Parameter estimates were made using the Dynamical Simple Model of Atmospheric Chemical Complexity (DSMACC box model, simple plume dispersion simulations, and the 3-D Meso-NH (non-hydrostatic mesoscale atmospheric model. In order to assess the impact of the LNOx plume approach on the NOx and O3 distributions on a large scale, simulations for the year 2006 were performed using the GEOS-Chem global model with a horizontal resolution of 2° × 2.5°. The implementation of the LNOx parameterization implies an NOx and O3 decrease on a large scale over the region characterized by a strong lightning activity (up to 25 and 8 %, respectively, over central Africa in July and a relative increase downwind of LNOx emissions (up to 18 and 2 % for NOx and O3, respectively, in July. The calculated variability in NOx and O3 mixing ratios around the mean value according to the known uncertainties in the parameter estimates is at a maximum over continental tropical regions with ΔNOx [−33.1, +29.7] ppt and ΔO3 [−1.56, +2.16] ppb, in January, and ΔNOx [−14.3, +21] ppt and ΔO3 [−1.18, +1.93] ppb, in July, mainly depending on the determination of the diffusion properties of the atmosphere and the initial NO mixing ratio injected by lightning. This approach allows us (i to reproduce a more realistic lightning NOx chemistry leading to better NOx and O3 distributions on the large scale and (ii to focus on other improvements to reduce remaining uncertainties from processes

Quasi-chemical approach for adsorption of mixtures with non-additive lateral interactions

Energy Technology Data Exchange (ETDEWEB)

Pinto, O.A. [Instituto de Bionanotecnología (INBIONATEC-CONICET), Universidad Nacional de Santiago de Estero, RN 9 Km 1125 Villa el Zanjón, Santiago del Estero G4206XCP (Argentina); Pasinetti, P.M., E-mail: pmp@unsl.edu.ar [Departamento de Física, Instituto de Física Aplicada (INFAP), Universidad Nacional de San Luis—CONICET, Ejército de los Andes 950, D5700BWS San Luis (Argentina); Ramirez-Pastor, A.J. [Departamento de Física, Instituto de Física Aplicada (INFAP), Universidad Nacional de San Luis—CONICET, Ejército de los Andes 950, D5700BWS San Luis (Argentina)

2017-01-15

Highlights: • The classical quasi-chemical approach is generalized to model non-additive mixtures. • The formalism allows to obtain the partial isotherms and the differential heat of adsorption. • A rich variety of low-temperature phases is observed in the adsorbed layer. • Theoretical results show a good agreement with Monte Carlo simulations. - Abstract: The statistical thermodynamics of binary mixtures with non-additive lateral interactions was developed on a generalization in the spirit of the lattice-gas model and the classical quasi-chemical approximation (QCA). The traditional assumption of a strictly pairwise additive nearest-neighbors interaction is replaced by a more general one, namely that the bond linking a certain atom with any of its neighbors depends considerably on how many of them are actually present (or absent) on the sites in the first coordination shell of the atom. The total and partial adsorption isotherms are given for both attractive and repulsive lateral interactions between the adsorbed species. Interesting behaviors are observed and discussed in terms of the low-temperature phases formed in the system. Comparisons with Monte Carlo simulations are performed in order to test the validity of the theoretical model.

Personalized Education Approaches for Chemical Engineering and Relevant Majors

Directory of Open Access Journals (Sweden)

Zhao Feng-qing

2016-01-01

Full Text Available Personalized education has drawn increasing attention in universities these years. With the purpose of improving the studentss’ comprehensive ability and developing teaching strategies to ensure students’ education is tailored to their needs, we proposed Three-Stage Approach (TSA to enhance personalized education for chemical engineering and relevant majors: professional tutorial system--equipping with professional guidance teachers for freshman students to guide their learning activities and provide professional guidance; open experimental project--setting up open experimental projects for sophomore and junior students to choose freely; individualized education module--setting up 10 different individualized education modules for senior students to select. After years of practice, the personalized education model is improved day by day and proved effective and fruitful.

Prediction of Chemical Function: Model Development and ...

Science.gov (United States)

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

The Conceptual Change Approach to Teaching Chemical Equilibrium

Science.gov (United States)

Canpolat, Nurtac; Pinarbasi, Tacettin; Bayrakceken, Samih; Geban, Omer

2006-01-01

This study investigates the effect of a conceptual change approach over traditional instruction on students' understanding of chemical equilibrium concepts (e.g. dynamic nature of equilibrium, definition of equilibrium constant, heterogeneous equilibrium, qualitative interpreting of equilibrium constant, changing the reaction conditions). This…

Chemical evolution of Local Group dwarf galaxies in a cosmological context - I. A new modelling approach and its application to the Sculptor dwarf spheroidal galaxy

Science.gov (United States)

Romano, Donatella; Starkenburg, Else

2013-09-01

We present a new approach for chemical evolution modelling, specifically designed to investigate the chemical properties of dwarf galaxies in a full cosmological framework. In particular, we focus on the Sculptor dwarf spheroidal galaxy, for which a wealth of observational data exists, as a test bed for our model. We select four candidate Sculptor-like galaxies from the satellite galaxy catalogue generated by implementation of a version of the Munich semi-analytic model for galaxy formation on the level 2 Aquarius dark matter simulations and use the mass assembly and star formation histories predicted for these four systems as an input for the chemical evolution code. We follow explicitly the evolution of several chemical elements, both in the cold gas out of which the stars form and in the hot medium residing in the halo. We take into account in detail the lifetimes of stars of different initial masses, the distribution of the delay times for Type Ia supernova explosions and the dependence of the stellar yields from the initial metallicity of the stars. We allow large fractions of metals to be deposited into the hot phase, either directly as stars die or through reheated gas flows powered by supernova explosions. We find that, in order to reproduce both the observed metallicity distribution function and the observed abundance ratios of long-lived stars of Sculptor, large fractions of the reheated metals must never re-enter regions of active star formation. With this prescription, all the four analogues to the Sculptor dwarf spheroidal galaxy extracted from the simulated satellites catalogue on the basis of luminosity and stellar population ages are found to reasonably match the detailed chemical properties of real Sculptor stars. However, all model galaxies do severely underestimate the fraction of very metal poor stars observed in Sculptor. Our analysis thus sets further constraints on the semi-analytical models and, at large, on possible metal enrichment

A kinetic model for chemical neurotransmission

Science.gov (United States)

Ramirez-Santiago, Guillermo; Martinez-Valencia, Alejandro; Fernandez de Miguel, Francisco

Recent experimental observations in presynaptic terminals at the neuromuscular junction indicate that there are stereotyped patterns of cooperativeness in the fusion of adjacent vesicles. That is, a vesicle in hemifusion process appears on the side of a fused vesicle and which is followed by another vesicle in a priming state while the next one is in a docking state. In this talk we present a kinetic model for this morphological pattern in which each vesicle state previous to the exocytosis is represented by a kinetic state. This chain states kinetic model can be analyzed by means of a Master equation whose solution is simulated with the stochastic Gillespie algorithm. With this approach we have reproduced the responses to the basal release in the absence of stimulation evoked by the electrical activity and the phenomena of facilitation and depression of neuromuscular synapses. This model offers new perspectives to understand the underlying phenomena in chemical neurotransmission based on molecular interactions that result in the cooperativity between vesicles during neurotransmitter release. DGAPA Grants IN118410 and IN200914 and Conacyt Grant 130031.

Approaches to surface complexation modeling of Uranium(VI) adsorption on aquifer sediments

Science.gov (United States)

Davis, J.A.; Meece, D.E.; Kohler, M.; Curtis, G.P.

2004-01-01

Uranium(VI) adsorption onto aquifer sediments was studied in batch experiments as a function of pH and U(VI) and dissolved carbonate concentrations in artificial groundwater solutions. The sediments were collected from an alluvial aquifer at a location upgradient of contamination from a former uranium mill operation at Naturita, Colorado (USA). The ranges of aqueous chemical conditions used in the U(VI) adsorption experiments (pH 6.9 to 7.9; U(VI) concentration 2.5 ?? 10-8 to 1 ?? 10-5 M; partial pressure of carbon dioxide gas 0.05 to 6.8%) were based on the spatial variation in chemical conditions observed in 1999-2000 in the Naturita alluvial aquifer. The major minerals in the sediments were quartz, feldspars, and calcite, with minor amounts of magnetite and clay minerals. Quartz grains commonly exhibited coatings that were greater than 10 nm in thickness and composed of an illite-smectite clay with occluded ferrihydrite and goethite nanoparticles. Chemical extractions of quartz grains removed from the sediments were used to estimate the masses of iron and aluminum present in the coatings. Various surface complexation modeling approaches were compared in terms of the ability to describe the U(VI) experimental data and the data requirements for model application to the sediments. Published models for U(VI) adsorption on reference minerals were applied to predict U(VI) adsorption based on assumptions about the sediment surface composition and physical properties (e.g., surface area and electrical double layer). Predictions from these models were highly variable, with results overpredicting or underpredicting the experimental data, depending on the assumptions used to apply the model. Although the models for reference minerals are supported by detailed experimental studies (and in ideal cases, surface spectroscopy), the results suggest that errors are caused in applying the models directly to the sediments by uncertain knowledge of: 1) the proportion and types of

Chemical reaction rates and non-equilibrium pressure of reacting gas mixtures in the state-to-state approach

International Nuclear Information System (INIS)

Kustova, Elena V.; Kremer, Gilberto M.

2014-01-01

Highlights: • State-to-state approach for coupled vibrational relaxation and chemical reactions. • Self-consistent model for rates of non-equilibrium reactions and energy transitions. • In viscous flows mass action law is violated. • Cross coupling between reaction rates and non-equilibrium pressure in viscous flow. • Results allow implementing the state-to-state approach for viscous flow simulations. - Abstract: Viscous gas flows with vibrational relaxation and chemical reactions in the state-to-state approach are analyzed. A modified Chapman–Enskog method is used for the determination of chemical reaction and vibrational transition rates and non-equilibrium pressure. Constitutive equations depend on the thermodynamic forces: velocity divergence and chemical reaction/transition affinity. As an application, N 2 flow with vibrational relaxation across a shock wave is investigated. Two distinct processes occur behind the shock: for small values of the distance the affinity is large and vibrational relaxation is in its initial stage; for large distances the affinity is small and the chemical reaction is in its final stage. The affinity contributes more to the transition rate than the velocity divergence and the effect of these two contributions are more important for small distances from the shock front. For the non-equilibrium pressure, the term associated with the bulk viscosity increases by a small amount the hydrostatic pressure

Chemical reaction rates and non-equilibrium pressure of reacting gas mixtures in the state-to-state approach

Energy Technology Data Exchange (ETDEWEB)

Kustova, Elena V., E-mail: e.kustova@spbu.ru [Department of Mathematics and Mechanics, Saint Petersburg State University, 198504 Universitetskiy pr. 28, Saint Petersburg (Russian Federation); Kremer, Gilberto M., E-mail: kremer@fisica.ufpr.br [Departamento de Física, Universidade Federal do Paraná, Caixa Postal 19044, 81531-980 Curitiba (Brazil)

2014-12-05

Highlights: • State-to-state approach for coupled vibrational relaxation and chemical reactions. • Self-consistent model for rates of non-equilibrium reactions and energy transitions. • In viscous flows mass action law is violated. • Cross coupling between reaction rates and non-equilibrium pressure in viscous flow. • Results allow implementing the state-to-state approach for viscous flow simulations. - Abstract: Viscous gas flows with vibrational relaxation and chemical reactions in the state-to-state approach are analyzed. A modified Chapman–Enskog method is used for the determination of chemical reaction and vibrational transition rates and non-equilibrium pressure. Constitutive equations depend on the thermodynamic forces: velocity divergence and chemical reaction/transition affinity. As an application, N{sub 2} flow with vibrational relaxation across a shock wave is investigated. Two distinct processes occur behind the shock: for small values of the distance the affinity is large and vibrational relaxation is in its initial stage; for large distances the affinity is small and the chemical reaction is in its final stage. The affinity contributes more to the transition rate than the velocity divergence and the effect of these two contributions are more important for small distances from the shock front. For the non-equilibrium pressure, the term associated with the bulk viscosity increases by a small amount the hydrostatic pressure.

SHEDS-HT: An Integrated Probabilistic Exposure Model for Prioritizing Exposures to Chemicals with Near-Field and Dietary Sources

Science.gov (United States)

United States Environmental Protection Agency (USEPA) researchers are developing a strategy for highthroughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologi...

An approach to the determination of physical-chemical limits of energy consumption for the transition to a stationary state

International Nuclear Information System (INIS)

Zimen, K.E.

1975-02-01

The paper gives a model of energy consumption and a programme for its application. Previous models are mainly criticized on the grounds that new technological developments as well as adjustments due to learning processes of homo sapiens are generally not sufficiently accounted for in these models. The approach of this new model is therefore an attempt at the determination of the physical-chemical limiting values for the capacity of the global HST (homo sapiens - Tellus) system or of individual regions with respect to certain critical factors. These limiting values determined by the physical-chemical system of the earth are independent of human ingenuity and flexibility. (orig./AK) [de

Modelling of the chemical state in groundwater infiltration systems

International Nuclear Information System (INIS)

Zysset, A.

1993-01-01

Groundwater is replenished by water stemming either from precipitations, lakes or rivers. The area where such an infiltration occurs is characterized by a change in the environmental conditions, such as a decrease of the flow velocity and an increase in the solid surface marking the boundary of the flow field. With these changes new chemical processes may become relevant to the transport behavior of contaminants. Since the rates of chemical processes usually are a function of the concentrations of several species, an understanding of infiltration sites may require a multicomponent approach. The present study aims at formulating a mathematical model together with its numerical solution for groundwater infiltration sites. Such a model should improve the understanding of groundwater quality changes related to infiltrating contaminants. The groundwater quality is of vital interest to men because at many places most of the drinking water originates from groundwater. In the first part of the present study two partial models are formulated: one accounting for the transport in a one-dimensional, homogeneous and saturated porous medium, the other accounting for chemical reactions. This second model is initially stated for general kinetic systems. Then, it is specified for two systems, namely for a system governed only by reactions which are fast compared to the transport processes and for a system with biologically mediated redox reactions of dissolved substrates. In the second part of the study a numerical solution to the model is developed. For this purpose, the two partial models are coupled. The coupling is either iterative as in the case of a system with fast reactions or sequential as in all other cases. The numerical solutions of simple test cases are compared to analytical solutions. In the third part the model is evaluated using observations of infiltration sites reported in the literature. (author) figs., tabs., 155 refs

Applicability of western chemical dietary exposure models to the Chinese population.

Science.gov (United States)

Zhao, Shizhen; Price, Oliver; Liu, Zhengtao; Jones, Kevin C; Sweetman, Andrew J

2015-07-01

A range of exposure models, which have been developed in Europe and North America, are playing an increasingly important role in priority setting and the risk assessment of chemicals. However, the applicability of these tools, which are based on Western dietary exposure pathways, to estimate chemical exposure to the Chinese population to support the development of a risk-based environment and exposure assessment, is unclear. Three frequently used modelling tools, EUSES, RAIDAR and ACC-HUMANsteady, have been evaluated in terms of human dietary exposure estimation by application to a range of chemicals with different physicochemical properties under both model default and Chinese dietary scenarios. Hence, the modelling approaches were assessed by considering dietary pattern differences only. The predicted dietary exposure pathways were compared under both scenarios using a range of hypothetical and current emerging contaminants. Although the differences across models are greater than those between dietary scenarios, model predictions indicated that dietary preference can have a significant impact on human exposure, with the relatively high consumption of vegetables and cereals resulting in higher exposure via plants-based foodstuffs under Chinese consumption patterns compared to Western diets. The selected models demonstrated a good ability to identify key dietary exposure pathways which can be used for screening purposes and an evaluative risk assessment. However, some model adaptations will be required to cover a number of important Chinese exposure pathways, such as freshwater farmed-fish, grains and pork. Copyright © 2015 Elsevier Inc. All rights reserved.

Chemical equilibrium models of interstellar gas clouds

International Nuclear Information System (INIS)

Freeman, A.

1982-10-01

This thesis contains work which helps towards our understanding of the chemical processes and astrophysical conditions in interstellar clouds, across the whole range of cloud types. The object of the exercise is to construct a mathematical model representing a large system of two-body chemical reactions in order to deduce astrophysical parameters and predict molecular abundances and chemical pathways. Comparison with observations shows that this type of model is valid but also indicates that our knowledge of some chemical reactions is incomplete. (author)

Aquatic exposures of chemical mixtures in urban environments: Approaches to impact assessment.

Science.gov (United States)

de Zwart, Dick; Adams, William; Galay Burgos, Malyka; Hollender, Juliane; Junghans, Marion; Merrington, Graham; Muir, Derek; Parkerton, Thomas; De Schamphelaere, Karel A C; Whale, Graham; Williams, Richard

2018-03-01

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes, from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the event mean concentration concept, with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modeling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed of the role of nonchemical stressors in such highly modified urban water bodies. Environ Toxicol Chem 2018;37:703-714. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

Directory of Open Access Journals (Sweden)

Aleksandar Sabljic

2004-12-01

Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

Life cycle impact assessment modeling for particulate matter: A new approach based on physico-chemical particle properties.

Science.gov (United States)

Notter, Dominic A

2015-09-01

Particulate matter (PM) causes severe damage to human health globally. Airborne PM is a mixture of solid and liquid droplets suspended in air. It consists of organic and inorganic components, and the particles of concern range in size from a few nanometers to approximately 10μm. The complexity of PM is considered to be the reason for the poor understanding of PM and may also be the reason why PM in environmental impact assessment is poorly defined. Currently, life cycle impact assessment is unable to differentiate highly toxic soot particles from relatively harmless sea salt. The aim of this article is to present a new impact assessment for PM where the impact of PM is modeled based on particle physico-chemical properties. With the new method, 2781 characterization factors that account for particle mass, particle number concentration, particle size, chemical composition and solubility were calculated. Because particle sizes vary over four orders of magnitudes, a sound assessment of PM requires that the exposure model includes deposition of particles in the lungs and that the fate model includes coagulation as a removal mechanism for ultrafine particles. The effects model combines effects from particle size, solubility and chemical composition. The first results from case studies suggest that PM that stems from emissions generally assumed to be highly toxic (e.g. biomass combustion and fossil fuel combustion) might lead to results that are similar compared with an assessment of PM using established methods. However, if harmless PM emissions are emitted, established methods enormously overestimate the damage. The new impact assessment allows a high resolution of the damage allocatable to different size fractions or chemical components. This feature supports a more efficient optimization of processes and products when combating air pollution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantum Chemical Modeling of Enzymatic Reactions: The Case of Decarboxylation.

Science.gov (United States)

Liao, Rong-Zhen; Yu, Jian-Guo; Himo, Fahmi

2011-05-10

We present a systematic study of the decarboxylation step of the enzyme aspartate decarboxylase with the purpose of assessing the quantum chemical cluster approach for modeling this important class of decarboxylase enzymes. Active site models ranging in size from 27 to 220 atoms are designed, and the barrier and reaction energy of this step are evaluated. To model the enzyme surrounding, homogeneous polarizable medium techniques are used with several dielectric constants. The main conclusion is that when the active site model reaches a certain size, the solvation effects from the surroundings saturate. Similar results have previously been obtained from systematic studies of other classes of enzymes, suggesting that they are of a quite general nature.

Target identification of natural and traditional medicines with quantitative chemical proteomics approaches.

Science.gov (United States)

Wang, Jigang; Gao, Liqian; Lee, Yew Mun; Kalesh, Karunakaran A; Ong, Yong Siang; Lim, Jaehong; Jee, Joo-Eun; Sun, Hongyan; Lee, Su Seong; Hua, Zi-Chun; Lin, Qingsong

2016-06-01

Natural and traditional medicines, being a great source of drugs and drug leads, have regained wide interests due to the limited success of high-throughput screening of compound libraries in the past few decades and the recent technology advancement. Many drugs/bioactive compounds exert their functions through interaction with their protein targets, with more and more drugs showing their ability to target multiple proteins, thus target identification has an important role in drug discovery and biomedical research fields. Identifying drug targets not only furthers the understanding of the mechanism of action (MOA) of a drug but also reveals its potential therapeutic applications and adverse side effects. Chemical proteomics makes use of affinity chromatography approaches coupled with mass spectrometry to systematically identify small molecule-protein interactions. Although traditional affinity-based chemical proteomics approaches have made great progress in the identification of cellular targets and elucidation of MOAs of many bioactive molecules, nonspecific binding remains a major issue which may reduce the accuracy of target identification and may hamper the drug development process. Recently, quantitative proteomics approaches, namely, metabolic labeling, chemical labeling, or label-free approaches, have been implemented in target identification to overcome such limitations. In this review, we will summarize and discuss the recent advances in the application of various quantitative chemical proteomics approaches for the identification of targets of natural and traditional medicines. Copyright © 2016. Published by Elsevier Inc.

A stepwise approach for defining the applicability domain of SAR and QSAR models

DEFF Research Database (Denmark)

Dimitrov, Sabcho; Dimitrova, Gergana; Pavlov, Todor

2005-01-01

A stepwise approach for determining the model applicability domain is proposed. Four stages are applied to account for the diversity and complexity of the current SAR/QSAR models, reflecting their mechanistic rationality (including metabolic activation of chemicals) and transparency. General para...

To Model Chemical Reactivity in Heterogeneous Emulsions, Think Homogeneous Microemulsions.

Science.gov (United States)

Bravo-Díaz, Carlos; Romsted, Laurence Stuart; Liu, Changyao; Losada-Barreiro, Sonia; Pastoriza-Gallego, Maria José; Gao, Xiang; Gu, Qing; Krishnan, Gunaseelan; Sánchez-Paz, Verónica; Zhang, Yongliang; Dar, Aijaz Ahmad

2015-08-25

Two important and unsolved problems in the food industry and also fundamental questions in colloid chemistry are how to measure molecular distributions, especially antioxidants (AOs), and how to model chemical reactivity, including AO efficiency in opaque emulsions. The key to understanding reactivity in organized surfactant media is that reaction mechanisms are consistent with a discrete structures-separate continuous regions duality. Aggregate structures in emulsions are determined by highly cooperative but weak organizing forces that allow reactants to diffuse at rates approaching their diffusion-controlled limit. Reactant distributions for slow thermal bimolecular reactions are in dynamic equilibrium, and their distributions are proportional to their relative solubilities in the oil, interfacial, and aqueous regions. Our chemical kinetic method is grounded in thermodynamics and combines a pseudophase model with methods for monitoring the reactions of AOs with a hydrophobic arenediazonium ion probe in opaque emulsions. We introduce (a) the logic and basic assumptions of the pseudophase model used to define the distributions of AOs among the oil, interfacial, and aqueous regions in microemulsions and emulsions and (b) the dye derivatization and linear sweep voltammetry methods for monitoring the rates of reaction in opaque emulsions. Our results show that this approach provides a unique, versatile, and robust method for obtaining quantitative estimates of AO partition coefficients or partition constants and distributions and interfacial rate constants in emulsions. The examples provided illustrate the effects of various emulsion properties on AO distributions such as oil hydrophobicity, emulsifier structure and HLB, temperature, droplet size, surfactant charge, and acidity on reactant distributions. Finally, we show that the chemical kinetic method provides a natural explanation for the cut-off effect, a maximum followed by a sharp reduction in AO efficiency with

Cellular automaton model of mass transport with chemical reactions

International Nuclear Information System (INIS)

Karapiperis, T.; Blankleider, B.

1993-10-01

The transport and chemical reactions of solutes are modelled as a cellular automaton in which molecules of different species perform a random walk on a regular lattice and react according to a local probabilistic rule. The model describes advection and diffusion in a simple way, and as no restriction is placed on the number of particles at a lattice site, it is also able to describe a wide variety of chemical reactions. Assuming molecular chaos and a smooth density function, we obtain the standard reaction-transport equations in the continuum limit. Simulations on one-and two-dimensional lattices show that the discrete model can be used to approximate the solutions of the continuum equations. We discuss discrepancies which arise from correlations between molecules and how these discrepancies disappear as the continuum limit is approached. Of particular interest are simulations displaying long-time behaviour which depends on long-wavelength statistical fluctuations not accounted for by the standard equations. The model is applied to the reactions a + b ↔ c and a + b → c with homogeneous and inhomogeneous initial conditions as well as to systems subject to autocatalytic reactions and displaying spontaneous formation of spatial concentration patterns. (author) 9 figs., 34 refs

Predicting the carcinogenicity of chemicals with alternative approaches: recent advances.

Science.gov (United States)

Benigni, Romualdo

2014-09-01

Alternative approaches to the rodent bioassay are necessary for early identification of problematic drugs and biocides during the development process, and are the only practicable tool for assessing environmental chemicals with no or adequate safety documentation. This review informs on: i) the traditional prescreening through genotoxicity testing; ii) an integrative approach that assesses DNA-reactivity and ability to disorganize tissues; iii) new applications of omics technologies (ToxCast/Tox21 project); iv) a pragmatic approach aimed at filling data gaps by intrapolating/extrapolating from similar chemicals (read-across, category formation). The review also approaches the issue of the concerns about false-positive and false-negative results that prevents a wider acceptance and use of alternatives. The review addresses strengths and limitations of various proposals, and concludes on the need of differential approaches to the issue of false negatives and false positives. False negatives can be eliminated or reduced below the variability of the animal assay with conservative quantitative structure-activity relationships or in vitro tests; false positives can be cleared with ad hoc mechanistically based follow-ups. This framework can permit a reduction of animal testing and a better protection of human health.

Modeling non-isothermal multiphase multi-species reactive chemical transport in geologic media

Energy Technology Data Exchange (ETDEWEB)

Tianfu Xu; Gerard, F.; Pruess, K.; Brimhall, G.

1997-07-01

The assessment of mineral deposits, the analysis of hydrothermal convection systems, the performance of radioactive, urban and industrial waste disposal, the study of groundwater pollution, and the understanding of natural groundwater quality patterns all require modeling tools that can consider both the transport of dissolved species as well as their interactions with solid (or other) phases in geologic media and engineered barriers. Here, a general multi-species reactive transport formulation has been developed, which is applicable to homogeneous and/or heterogeneous reactions that can proceed either subject to local equilibrium conditions or kinetic rates under non-isothermal multiphase flow conditions. Two numerical solution methods, the direct substitution approach (DSA) and sequential iteration approach (SIA) for solving the coupled complex subsurface thermo-physical-chemical processes, are described. An efficient sequential iteration approach, which solves transport of solutes and chemical reactions sequentially and iteratively, is proposed for the current reactive chemical transport computer code development. The coupled flow (water, vapor, air and heat) and solute transport equations are also solved sequentially. The existing multiphase flow code TOUGH2 and geochemical code EQ3/6 are used to implement this SIA. The flow chart of the coupled code TOUGH2-EQ3/6, required modifications of the existing codes and additional subroutines needed are presented.

Security risk assessment and protection in the chemical and process industry

OpenAIRE

Reniers, Genserik; van Lerberghe, Paul; van Gulijk, Coen

2014-01-01

This article describes a security risk assessment and protection methodology that was developed for use in the chemical- and process industry in Belgium. The approach of the method follows a risk-based approach that follows desing principles for chemical safety. That approach is beneficial for workers in the chemical industry because they recognize the steps in this model from familiar safety models .The model combines the rings-of-protection approach with generic security practices including...

Poromechanics Parameters of Fluid-Saturated Chemically Active Fibrous Media Derived from a Micromechanical Approach.

Science.gov (United States)

Misra, Anil; Parthasarathy, Ranganathan; Singh, Viraj; Spencer, Paulette

2013-01-01

The authors have derived macroscale poromechanics parameters for chemically active saturated fibrous media by combining microstructure-based homogenization with Hill's volume averaging. The stress-strain relationship of the dry fibrous media is first obtained by considering the fiber behavior. The constitutive relationships applicable to saturated media are then derived in the poromechanics framework using Hill's Lemmas. The advantage of this approach is that the resultant continuum model assumes a form suited to study porous materials, while retaining the effect of discrete fiber deformation. As a result, the model is able to predict the influence of microscale phenomena such as fiber buckling on the overall behavior, and in particular, on the poromechanics constants. The significance of the approach is demonstrated using the effect of drainage and fiber nonlinearity on monotonic compressive stress-strain behavior. The model predictions conform to the experimental observations for articular cartilage. The method can potentially be extended to other porous materials such as bone, clays, foams, and concrete.

SHEDS-HT: an integrated probabilistic exposure model for prioritizing exposures to chemicals with near-field and dietary sources.

Science.gov (United States)

Isaacs, Kristin K; Glen, W Graham; Egeghy, Peter; Goldsmith, Michael-Rock; Smith, Luther; Vallero, Daniel; Brooks, Raina; Grulke, Christopher M; Özkaynak, Halûk

2014-11-04

United States Environmental Protection Agency (USEPA) researchers are developing a strategy for high-throughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologically relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. Based on probabilistic methods and algorithms developed for The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals (SHEDS-MM), a new mechanistic modeling approach has been developed to accommodate high-throughput (HT) assessment of exposure potential. In this SHEDS-HT model, the residential and dietary modules of SHEDS-MM have been operationally modified to reduce the user burden, input data demands, and run times of the higher-tier model, while maintaining critical features and inputs that influence exposure. The model has been implemented in R; the modeling framework links chemicals to consumer product categories or food groups (and thus exposure scenarios) to predict HT exposures and intake doses. Initially, SHEDS-HT has been applied to 2507 organic chemicals associated with consumer products and agricultural pesticides. These evaluations employ data from recent USEPA efforts to characterize usage (prevalence, frequency, and magnitude), chemical composition, and exposure scenarios for a wide range of consumer products. In modeling indirect exposures from near-field sources, SHEDS-HT employs a fugacity-based module to estimate concentrations in indoor environmental media. The concentration estimates, along with relevant exposure factors and human activity data, are then used by the model to rapidly generate probabilistic population distributions of near-field indirect exposures via dermal, nondietary ingestion, and inhalation pathways. Pathway-specific estimates of near-field direct exposures from consumer products are also modeled

Rich Ground State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters

DEFF Research Database (Denmark)

Larsen, Peter Mahler; Jacobsen, Karsten Wedel; Schiøtz, Jakob

2018-01-01

We show that nanoparticles can have very rich ground state chemical order. This is illustrated by determining the chemical ordering of Ag-Au 309-atom Mackay icosahedral nanoparticles. The energy of the nanoparticles is described using a cluster expansion model, and a Mixed Integer Programming (MIP......) approach is used to find the exact ground state configurations for all stoichiometries. The chemical ordering varies widely between the different stoichiometries, and display a rich zoo of structures with non-trivial ordering....

Towards predictive resistance models for agrochemicals by combining chemical and protein similarity via proteochemometric modelling.

Science.gov (United States)

van Westen, Gerard J P; Bender, Andreas; Overington, John P

2014-10-01

Resistance to pesticides is an increasing problem in agriculture. Despite practices such as phased use and cycling of 'orthogonally resistant' agents, resistance remains a major risk to national and global food security. To combat this problem, there is a need for both new approaches for pesticide design, as well as for novel chemical entities themselves. As summarized in this opinion article, a technique termed 'proteochemometric modelling' (PCM), from the field of chemoinformatics, could aid in the quantification and prediction of resistance that acts via point mutations in the target proteins of an agent. The technique combines information from both the chemical and biological domain to generate bioactivity models across large numbers of ligands as well as protein targets. PCM has previously been validated in prospective, experimental work in the medicinal chemistry area, and it draws on the growing amount of bioactivity information available in the public domain. Here, two potential applications of proteochemometric modelling to agrochemical data are described, based on previously published examples from the medicinal chemistry literature.

AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

Science.gov (United States)

A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

Quantum chemical modeling of zeolite-catalyzed methylation reactions: toward chemical accuracy for barriers.

Science.gov (United States)

Svelle, Stian; Tuma, Christian; Rozanska, Xavier; Kerber, Torsten; Sauer, Joachim

2009-01-21

The methylation of ethene, propene, and t-2-butene by methanol over the acidic microporous H-ZSM-5 catalyst has been investigated by a range of computational methods. Density functional theory (DFT) with periodic boundary conditions (PBE functional) fails to describe the experimentally determined decrease of apparent energy barriers with the alkene size due to inadequate description of dispersion forces. Adding a damped dispersion term expressed as a parametrized sum over atom pair C(6) contributions leads to uniformly underestimated barriers due to self-interaction errors. A hybrid MP2:DFT scheme is presented that combines MP2 energy calculations on a series of cluster models of increasing size with periodic DFT calculations, which allows extrapolation to the periodic MP2 limit. Additionally, errors caused by the use of finite basis sets, contributions of higher order correlation effects, zero-point vibrational energy, and thermal contributions to the enthalpy were evaluated and added to the "periodic" MP2 estimate. This multistep approach leads to enthalpy barriers at 623 K of 104, 77, and 48 kJ/mol for ethene, propene, and t-2-butene, respectively, which deviate from the experimentally measured values by 0, +13, and +8 kJ/mol. Hence, enthalpy barriers can be calculated with near chemical accuracy, which constitutes significant progress in the quantum chemical modeling of reactions in heterogeneous catalysis in general and microporous zeolites in particular.

Equilibrium approach towards water resource management and pollution control in coal chemical industrial park.

Science.gov (United States)

Xu, Jiuping; Hou, Shuhua; Xie, Heping; Lv, Chengwei; Yao, Liming

2018-08-01

In this study, an integrated water and waste load allocation model is proposed to assist decision makers in better understanding the trade-offs between economic growth, resource utilization, and environmental protection of coal chemical industries which characteristically have high water consumption and pollution. In the decision framework, decision makers in a same park, each of whom have different goals and preferences, work together to seek a collective benefit. Similar to a Stackelberg-Nash game, the proposed approach illuminates the decision making interrelationships and involves in the conflict coordination between the park authority and the individual coal chemical company stockholders. In the proposed method, to response to climate change and other uncertainties, a risk assessment tool, Conditional Value-at-Risk (CVaR) and uncertainties through reflecting parameters and coefficients using probability and fuzzy set theory are integrated in the modeling process. Then a case study from Yuheng coal chemical park is presented to demonstrate the practicality and efficiency of the optimization model. To reasonable search the potential consequences of different responses to water and waste load allocation strategies, a number of scenario results considering environmental uncertainty and decision maker' attitudes are examined to explore the tradeoffs between economic development and environmental protection and decision makers' objectives. The results are helpful for decision/police makers to adjust current strategies adapting for current changes. Based on the scenario analyses and discussion, some propositions and operational policies are given and sensitive adaptation strategies are presented to support the efficient, balanced and sustainable development of coal chemical industrial parks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish.

Science.gov (United States)

Mintram, Kate S; Brown, A Ross; Maynard, Samuel K; Thorbek, Pernille; Tyler, Charles R

2018-02-01

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Mathematical modeling a chemical engineer's perspective

CERN Document Server

Rutherford, Aris

1999-01-01

Mathematical modeling is the art and craft of building a system of equations that is both sufficiently complex to do justice to physical reality and sufficiently simple to give real insight into the situation. Mathematical Modeling: A Chemical Engineer's Perspective provides an elementary introduction to the craft by one of the century's most distinguished practitioners.Though the book is written from a chemical engineering viewpoint, the principles and pitfalls are common to all mathematical modeling of physical systems. Seventeen of the author's frequently cited papers are reprinted to illus

UNCERTAINTIES IN GALACTIC CHEMICAL EVOLUTION MODELS

International Nuclear Information System (INIS)

Côté, Benoit; Ritter, Christian; Herwig, Falk; O’Shea, Brian W.; Pignatari, Marco; Jones, Samuel; Fryer, Chris L.

2016-01-01

We use a simple one-zone galactic chemical evolution model to quantify the uncertainties generated by the input parameters in numerical predictions for a galaxy with properties similar to those of the Milky Way. We compiled several studies from the literature to gather the current constraints for our simulations regarding the typical value and uncertainty of the following seven basic parameters: the lower and upper mass limits of the stellar initial mass function (IMF), the slope of the high-mass end of the stellar IMF, the slope of the delay-time distribution function of Type Ia supernovae (SNe Ia), the number of SNe Ia per M ⊙ formed, the total stellar mass formed, and the final mass of gas. We derived a probability distribution function to express the range of likely values for every parameter, which were then included in a Monte Carlo code to run several hundred simulations with randomly selected input parameters. This approach enables us to analyze the predicted chemical evolution of 16 elements in a statistical manner by identifying the most probable solutions, along with their 68% and 95% confidence levels. Our results show that the overall uncertainties are shaped by several input parameters that individually contribute at different metallicities, and thus at different galactic ages. The level of uncertainty then depends on the metallicity and is different from one element to another. Among the seven input parameters considered in this work, the slope of the IMF and the number of SNe Ia are currently the two main sources of uncertainty. The thicknesses of the uncertainty bands bounded by the 68% and 95% confidence levels are generally within 0.3 and 0.6 dex, respectively. When looking at the evolution of individual elements as a function of galactic age instead of metallicity, those same thicknesses range from 0.1 to 0.6 dex for the 68% confidence levels and from 0.3 to 1.0 dex for the 95% confidence levels. The uncertainty in our chemical evolution model

A detailed chemical kinetic model for pyrolysis of the lignin model compound chroman

Directory of Open Access Journals (Sweden)

James Bland

2013-12-01

Full Text Available The pyrolysis of woody biomass, including the lignin component, is emerging as a potential technology for the production of renewable fuels and commodity chemicals. Here we describe the construction and implementation of an elementary chemical kinetic model for pyrolysis of the lignin model compound chroman and its reaction intermediate ortho-quinone methide (o-QM. The model is developed using both experimental and theoretical data, and represents a hybrid approach to kinetic modeling that has the potential to provide molecular level insight into reaction pathways and intermediates while accurately describing reaction rates and product formation. The kinetic model developed here can replicate all known aspects of chroman pyrolysis, and provides new information on elementary reaction steps. Chroman pyrolysis is found to proceed via an initial retro-Diels–Alder reaction to form o-QM + ethene (C2H4, followed by dissociation of o-QM to the C6H6 isomers benzene and fulvene (+ CO. At temperatures of around 1000–1200 K and above fulvene rapidly isomerizes to benzene, where an activation energy of around 270 kJ mol-1 is required to reproduce experimental observations. A new G3SX level energy surface for the isomerization of fulvene to benzene supports this result. Our modeling also suggests that thermal decomposition of fulvene may be important at around 950 K and above. This study demonstrates that theoretical protocols can provide a significant contribution to the development of kinetic models for biomass pyrolysis by elucidating reaction mechanisms, intermediates, and products, and also by supplying realistic rate coefficients and thermochemical properties.

Prioritising chemicals used in personal care products in China for environmental risk assessment: Application of the RAIDAR model

International Nuclear Information System (INIS)

Gouin, Todd; Egmond, Roger van; Price, Oliver R.; Hodges, Juliet E.N.

2012-01-01

China represents a significant market for the sale of personal care products (PCPs). Given the continuous emission of hundreds of chemicals used in PCPs to waste water and the aquatic environment after regular use, methods for prioritising the environmental risk assessment for China are needed. In an effort to assess the prioritisation of chemicals used in PCPs in China, we have identified the chemical ingredients used in 2500 PCPs released to the Chinese market in 2009, and estimated the annual emission of these chemicals. The physical-chemical property data for these substances have been estimated and used as model inputs in the RAIDAR model. In general, the RAIDAR model provides an overall assessment of the multimedia fate of chemicals, and provides a holistic approach for prioritising chemical ingredients. The prioritisation exercise conducted in this study is shown to be strongly influenced by loss processes, such as the removal efficiencies of WWT plants and biotransformation. - Highlights: ► Chemicals used in PCPs in China are prioritised using the RAIDAR model. ► Chemicals used in PCPs are estimated to have Risk assessment factors <<1. ► Loss processes strongly influence how chemicals are prioritised. - The application of the Risk IDentification And Ranking (RAIDAR) model is shown to be a potentially effective tool for prioritising chemicals used in personal care products in China.

Estimating surface water concentrations of “down-the-drain” chemicals in China using a global model

International Nuclear Information System (INIS)

Whelan, M.J.; Hodges, J.E.N.; Williams, R.J.; Keller, V.D.J.; Price, O.R.; Li, M.

2012-01-01

Predictions of surface water exposure to “down-the-drain” chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit “unit-world” approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to “down-the-drain” chemicals in China for different levels of sewage treatment provision. Predicted spatial patterns of concentration were consistent with observed water quality classes for China. - Highlights: ► A global-scale model of “down-the-drain” chemical concentrations is presented. ► The model was used to predict spatial patterns of exposure in China. ► Predictions were consistent with observed water quality classes. ► The model can identify hotspots and statistical distributions of concentrations. - A global-scale model was used to predict spatial patterns of “down-the-drain” chemical concentrations in China. Predictions were consistent with observed water quality classes, demonstrating the potential value of the model.

A TIERED APPROACH TO LIFE STAGES TESTING FOR AGRICULTURAL CHEMICAL SAFERY ASSESSMENT

Science.gov (United States)

A proposal has been developed by the Agricultural Chemical Safety Assessment (ACSA) Technical Committee of the ILSI Health and Environmental Sciences Institute (HESI) for an improved approach to assessing the safety of crop protection chemicals. The goal is to ensure that studie...

Fate modelling of chemical compounds with incomplete data sets

DEFF Research Database (Denmark)

Birkved, Morten; Heijungs, Reinout

2011-01-01

Impact assessment of chemical compounds in Life Cycle Impact Assessment (LCIA) and Environmental Risk Assessment (ERA) requires a vast amount of data on the properties of the chemical compounds being assessed. These data are used in multi-media fate and exposure models, to calculate risk levels...... in an approximate way. The idea is that not all data needed in a multi-media fate and exposure model are completely independent and equally important, but that there are physical-chemical and biological relationships between sets of chemical properties. A statistical model is constructed to underpin this assumption...... and other indicators. ERA typically addresses one specific chemical, but in an LCIA, the number of chemicals encountered may be quite high, up to hundreds or thousands. This study explores the development of meta-models, which are supposed to reflect the “true”multi-media fate and exposure model...

Coupling between cracking and chemical degradation in cement based materials: characterisation and modelling

International Nuclear Information System (INIS)

Tognazzi, C.

1998-01-01

The aim of this work is to study the durability of concretes used for radioactive waste storage. It has already been shown that the concrete degradation during a storage phenomenon is due to the attack of the cement barrier by the water of the host rock, at ambient temperature. The modelling of this chemical degradation is now validated for un-cracked materials. However, a concrete preexisting crack can exist. In this work, has then been particularly studied the influence of a crack on the long term chemical degradation. The studies have been carried out on a mortar cracked mechanically (in compression or traction) and chemically degraded by leaching (reference degradation) and by accelerated degradations (with ammonium nitrate or under electric field). The diffusion properties have been measured at each step of the experiment. They have been confronted with transfer models. Results have revealed the existence of a coupling between the preexisting crack and the chemical degradation. At last, a modelling of the chemical degradation for cement materials has been proposed and validated both for pure cement and for mortars, in the cases of simple leaching and of leaching with ammonium nitrate. Its application to cracked materials by a microscopic approach (crack described in the lattice) has allowed to specify the interpretation of the experimental results. (O.M.)

General approaches to the risk assessment of chemicals

Energy Technology Data Exchange (ETDEWEB)

Murphy, Patrick [Commission of the European Communities, Directorate General XI, Environment, Nuclear Safety and Civil Protection (Belgium)

1992-07-01

deciding upon the granting of permits for landfill sites or the discharge of toxic chemicals to water or air and in doing so they must take into account the hydrology, geology and climate of the specific locality. While the basic approach to chemical risk assessment will be the same, irrespective of the specific objective for which the assessment is carried out, the details will vary as a function of: the product type (pharmaceutical, pesticide, industrial chemical, etc.), the target population of interest (patient, environment, consumer, worker, etc.) and the exposure scenario (global, international, national, local)

General approaches to the risk assessment of chemicals

International Nuclear Information System (INIS)

Murphy, Patrick

1992-01-01

deciding upon the granting of permits for landfill sites or the discharge of toxic chemicals to water or air and in doing so they must take into account the hydrology, geology and climate of the specific locality. While the basic approach to chemical risk assessment will be the same, irrespective of the specific objective for which the assessment is carried out, the details will vary as a function of: the product type (pharmaceutical, pesticide, industrial chemical, etc.), the target population of interest (patient, environment, consumer, worker, etc.) and the exposure scenario (global, international, national, local)

Management of diabetic complications: a chemical constituents based approach.

Science.gov (United States)

Singh, Randhir; Kaur, Navpreet; Kishore, Lalit; Gupta, Girish Kumar

2013-10-28

Long term hyperglycemia leads to development of complications associated with diabetes. Diabetic complications are now a global health problem without effective therapeutic approach. Hyperglycemia and oxidative stress are important components for the development of diabetic complications. Over the past few decades, herbal medicines have attracted much attention as potential therapeutic agents in the prevention and treatment of diabetic complications due to their multiple targets and less toxic side effects. This review aims to assess the current available knowledge of medicinal herbs for attenuation and management of diabetic complications and their underlying mechanisms. Bibliographic investigation was carried out by scrutinizing classical text books and peer reviewed papers, consulting worldwide accepted scientific databases (SCOPUS, PUBMED, SCIELO, NISCAIR, Google Scholar) to retrieve available published literature. The inclusion criteria for the selection of plants were based upon all medicinal herbs and their active compounds with attributed potentials in relieving diabetic complications. Moreover, plants which have potential effect in ameliorating oxidative stress in diabetic animals have been included. Overall, 238 articles were reviewed for plant literature and out of the reviewed literature, 127 articles were selected for the study. Various medicinal plants/plant extracts containing flavonoids, alkaloids, phenolic compounds, terpenoids, saponins and phytosterol type chemical constituents were found to be effective in the management of diabetic complications. This effect might be attributed to amelioration of persistent hyperglycemia, oxidative stress and modulation of various metabolic pathways involved in the pathogenesis of diabetic complications. Screening chemical candidate from herbal medicine might be a promising approach for new drug discovery to treat the diabetic complications. There is still a dire need to explore the mechanism of action of

Modeling in transport phenomena a conceptual approach

CERN Document Server

Tosun, Ismail

2007-01-01

Modeling in Transport Phenomena, Second Edition presents and clearly explains with example problems the basic concepts and their applications to fluid flow, heat transfer, mass transfer, chemical reaction engineering and thermodynamics. A balanced approach is presented between analysis and synthesis, students will understand how to use the solution in engineering analysis. Systematic derivations of the equations and the physical significance of each term are given in detail, for students to easily understand and follow up the material. There is a strong incentive in science and engineering to

A New Approach to Joining Dissimilar Ceramic Oxides for Chemical Sensors

International Nuclear Information System (INIS)

Zhuiykov, Serge

2009-01-01

Conventional joining of dissimilar oxides for sensing electrodes (SE) of chemical sensors has been pivotal to the development of various sensors and is vital to their further development. However, it is shown that the uncertainty (of a fundamental nature) in the properties of dissimilar oxides in SE causes the determination of their sensing characteristics to be ambiguous. Characteristics are different for such controlled parameters as pyrolysis temperature, crystal structure, particle's morphology and size, chemical and phase composition, the coefficient of thermal expansion (CTE), surface architecture, the bulk and surface stoichiometry and type and conductivity of additives. Here, we provide an alternative approach for joining dissimilar metal-oxides for chemical sensors SE. The approach relies on the development of at least one transient liquid oxide phase on the ceramic-SE interface. These results constitute key points relevant to selection oxides for joining, sintering temperatures and heating/cooling temperature rates.

Systems approach to chemical spill response information needs

Energy Technology Data Exchange (ETDEWEB)

Parnarouskis, M.C.; Flessner, M.F.; Potts, R.G.

1980-01-01

The Chemical Hazards Response Information System (CHRIS) has been specifically designed to meet the emergency needs of US Coast Guard field personnel, currently providing them with information on 900 hazardous chemicals, with methods of predicting hazards resulting from accidental discharges, and with procedures for selecting and implementing response to accident discharges. The major components of CHRIS and the computerized hazard assessment models within the Hazard Assessment Computer System are described in detail.

Galactic chemical evolution in hierarchical formation models

Science.gov (United States)

Arrigoni, Matias

2010-10-01

The chemical properties and abundance ratios of galaxies provide important information about their formation histories. Galactic chemical evolution has been modelled in detail within the monolithic collapse scenario. These models have successfully described the abundance distributions in our Galaxy and other spiral discs, as well as the trends of metallicity and abundance ratios observed in early-type galaxies. In the last three decades, however, the paradigm of hierarchical assembly in a Cold Dark Matter (CDM) cosmology has revised the picture of how structure in the Universe forms and evolves. In this scenario, galaxies form when gas radiatively cools and condenses inside dark matter haloes, which themselves follow dissipationless gravitational collapse. The CDM picture has been successful at predicting many observed properties of galaxies (for example, the luminosity and stellar mass function of galaxies, color-magnitude or star formation rate vs. stellar mass distributions, relative numbers of early and late-type galaxies, gas fractions and size distributions of spiral galaxies, and the global star formation history), though many potential problems and open questions remain. It is therefore interesting to see whether chemical evolution models, when implemented within this modern cosmological context, are able to correctly predict the observed chemical properties of galaxies. With the advent of more powerfull telescopes and detectors, precise observations of chemical abundances and abundance ratios in various phases (stellar, ISM, ICM) offer the opportunity to obtain strong constraints on galaxy formation histories and the physics that shapes them. However, in order to take advantage of these observations, it is necessary to implement detailed modeling of chemical evolution into a modern cosmological model of hierarchical assembly.

Modelling Students' Visualisation of Chemical Reaction

Science.gov (United States)

Cheng, Maurice M. W.; Gilbert, John K.

2017-01-01

This paper proposes a model-based notion of "submicro representations of chemical reactions". Based on three structural models of matter (the simple particle model, the atomic model and the free electron model of metals), we suggest there are two major models of reaction in school chemistry curricula: (a) reactions that are simple…

The use of mental models in chemical risk protection: developing a generic workplace methodology.

Science.gov (United States)

Cox, Patrick; Niewöhmer, Jörg; Pidgeon, Nick; Gerrard, Simon; Fischhoff, Baruch; Riley, Donna

2003-04-01

We adopted a comparative approach to evaluate and extend a generic methodology to analyze the different sets of beliefs held about chemical hazards in the workplace. Our study mapped existing knowledge structures about the risks associated with the use of perchloroethylene and rosin-based solder flux in differing workplaces. "Influence diagrams" were used to represent beliefs held by chemical experts; "user models" were developed from data elicited from open-ended interviews with the workplace users of the chemicals. The juxtaposition of expert and user understandings of chemical risks enabled us to identify knowledge gaps and misunderstandings and to reinforce appropriate sets of safety beliefs and behavior relevant to chemical risk communications. By designing safety information to be more relevant to the workplace context of users, we believe that employers and employees may gain improved knowledge about chemical hazards in the workplace, such that better chemical risk management, self-protection, and informed decision making develop over time.

Evaluation of the applicability of the Benchmark approach to existing toxicological data. Framework: Chemical compounds in the working place

NARCIS (Netherlands)

Appel MJ; Bouman HGM; Pieters MN; Slob W; Adviescentrum voor chemische; CSR

2001-01-01

Five chemicals used in workplace, for which a risk assessment had already been carried out, were selected and the relevant critical studies re-analyzed by the Benchmark approach. The endpoints involved included continuous, and ordinal data. Dose-response modeling could be reasonablyapplied to the

Designing Solutions by a Student Centred Approach: Integration of Chemical Process Simulation with Statistical Tools to Improve Distillation Systems

Directory of Open Access Journals (Sweden)

Isabel M. Joao

2017-09-01

Full Text Available Projects thematically focused on simulation and statistical techniques for designing and optimizing chemical processes can be helpful in chemical engineering education in order to meet the needs of engineers. We argue for the relevance of the projects to improve a student centred approach and boost higher order thinking skills. This paper addresses the use of Aspen HYSYS by Portuguese chemical engineering master students to model distillation systems together with statistical experimental design techniques in order to optimize the systems highlighting the value of applying problem specific knowledge, simulation tools and sound statistical techniques. The paper summarizes the work developed by the students in order to model steady-state processes, dynamic processes and optimize the distillation systems emphasizing the benefits of the simulation tools and statistical techniques in helping the students learn how to learn. Students strengthened their domain specific knowledge and became motivated to rethink and improve chemical processes in their future chemical engineering profession. We discuss the main advantages of the methodology from the students’ and teachers perspective

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Science.gov (United States)

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Science.gov (United States)

Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

2014-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

Energy Technology Data Exchange (ETDEWEB)

Claveau, J; Ramaroson, R [Office National d` Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

1998-12-31

The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

Energy Technology Data Exchange (ETDEWEB)

Claveau, J.; Ramaroson, R. [Office National d`Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

1997-12-31

The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

A novel in vitro toxicological approach to identify chemicals with a prostate-mediated effect on male reproduction

Directory of Open Access Journals (Sweden)

S. Lorenzetti

2011-01-01

Full Text Available Prostate, an overlooked target in in vitro alternative methods, is critical for male fertility. Within the EU project ReProTect, the LNCaP cell line was used as a model system to screen chemicals affecting prostate by a tiered approach integrating two toxicological endpoints: cell viability and PSA secretion. A ReProTect training set of (anti androgenic chemicals affecting reproductive tissues were used. Androgens, and unexpectedly glufosinate ammonium, markedly increased PSA, whereas anti-androgens also increased PSA, but at a much lower magnitude than androgens. Our tiered approach properly discriminated androgenic compounds as well as yielded no false positives, as based on available toxicological evidences. The PSA secretion assay is directly linked to the prostate physiological function and it may integrate the information provided by mechanistic-based assays (i.e. AR binding and gene expression.

Chemical model reduction under uncertainty

KAUST Repository

Najm, Habib; Galassi, R. Malpica; Valorani, M.

2016-01-01

We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

Chemical model reduction under uncertainty

KAUST Repository

Najm, Habib

2016-01-05

We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

Quantum chemical approach for condensed-phase thermochemistry (V): Development of rigid-body type harmonic solvation model

Science.gov (United States)

Tarumi, Moto; Nakai, Hiromi

2018-05-01

This letter proposes an approximate treatment of the harmonic solvation model (HSM) assuming the solute to be a rigid body (RB-HSM). The HSM method can appropriately estimate the Gibbs free energy for condensed phases even where an ideal gas model used by standard quantum chemical programs fails. The RB-HSM method eliminates calculations for intra-molecular vibrations in order to reduce the computational costs. Numerical assessments indicated that the RB-HSM method can evaluate entropies and internal energies with the same accuracy as the HSM method but with lower calculation costs.

Medical mitigation model: quantifying the benefits of the public health response to a chemical terrorism attack.

Science.gov (United States)

Good, Kevin; Winkel, David; VonNiederhausern, Michael; Hawkins, Brian; Cox, Jessica; Gooding, Rachel; Whitmire, Mark

2013-06-01

The Chemical Terrorism Risk Assessment (CTRA) and Chemical Infrastructure Risk Assessment (CIRA) are programs that estimate the risk of chemical terrorism attacks to help inform and improve the US defense posture against such events. One aspect of these programs is the development and advancement of a Medical Mitigation Model-a mathematical model that simulates the medical response to a chemical terrorism attack and estimates the resulting number of saved or benefited victims. At the foundation of the CTRA/CIRA Medical Mitigation Model is the concept of stock-and-flow modeling; "stocks" are states that individuals progress through during the event, while "flows" permit and govern movement from one stock to another. Using this approach, the model is able to simulate and track individual victims as they progress from exposure to an end state. Some of the considerations in the model include chemical used, type of attack, route and severity of exposure, response-related delays, detailed treatment regimens with efficacy defined as a function of time, medical system capacity, the influx of worried well individuals, and medical countermeasure availability. As will be demonstrated, the output of the CTRA/CIRA Medical Mitigation Model makes it possible to assess the effectiveness of the existing public health response system and develop and examine potential improvement strategies. Such a modeling and analysis capability can be used to inform first-responder actions/training, guide policy decisions, justify resource allocation, and direct knowledge-gap studies.

Mass balance modelling of contaminants in river basins: a flexible matrix approach.

Science.gov (United States)

Warren, Christopher; Mackay, Don; Whelan, Mick; Fox, Kay

2005-12-01

A novel and flexible approach is described for simulating the behaviour of chemicals in river basins. A number (n) of river reaches are defined and their connectivity is described by entries in an n x n matrix. Changes in segmentation can be readily accommodated by altering the matrix entries, without the need for model revision. Two models are described. The simpler QMX-R model only considers advection and an overall loss due to the combined processes of volatilization, net transfer to sediment and degradation. The rate constant for the overall loss is derived from fugacity calculations for a single segment system. The more rigorous QMX-F model performs fugacity calculations for each segment and explicitly includes the processes of advection, evaporation, water-sediment exchange and degradation in both water and sediment. In this way chemical exposure in all compartments (including equilibrium concentrations in biota) can be estimated. Both models are designed to serve as intermediate-complexity exposure assessment tools for river basins with relatively low data requirements. By considering the spatially explicit nature of emission sources and the changes in concentration which occur with transport in the channel system, the approach offers significant advantages over simple one-segment simulations while being more readily applicable than more sophisticated, highly segmented, GIS-based models.

The Impact of Modeling Assumptions in Galactic Chemical Evolution Models

Science.gov (United States)

Côté, Benoit; O'Shea, Brian W.; Ritter, Christian; Herwig, Falk; Venn, Kim A.

2017-02-01

We use the OMEGA galactic chemical evolution code to investigate how the assumptions used for the treatment of galactic inflows and outflows impact numerical predictions. The goal is to determine how our capacity to reproduce the chemical evolution trends of a galaxy is affected by the choice of implementation used to include those physical processes. In pursuit of this goal, we experiment with three different prescriptions for galactic inflows and outflows and use OMEGA within a Markov Chain Monte Carlo code to recover the set of input parameters that best reproduces the chemical evolution of nine elements in the dwarf spheroidal galaxy Sculptor. This provides a consistent framework for comparing the best-fit solutions generated by our different models. Despite their different degrees of intended physical realism, we found that all three prescriptions can reproduce in an almost identical way the stellar abundance trends observed in Sculptor. This result supports the similar conclusions originally claimed by Romano & Starkenburg for Sculptor. While the three models have the same capacity to fit the data, the best values recovered for the parameters controlling the number of SNe Ia and the strength of galactic outflows, are substantially different and in fact mutually exclusive from one model to another. For the purpose of understanding how a galaxy evolves, we conclude that only reproducing the evolution of a limited number of elements is insufficient and can lead to misleading conclusions. More elements or additional constraints such as the Galaxy’s star-formation efficiency and the gas fraction are needed in order to break the degeneracy between the different modeling assumptions. Our results show that the successes and failures of chemical evolution models are predominantly driven by the input stellar yields, rather than by the complexity of the Galaxy model itself. Simple models such as OMEGA are therefore sufficient to test and validate stellar yields. OMEGA

Nitrate source apportionment using a combined dual isotope, chemical and bacterial property, and Bayesian model approach in river systems

Science.gov (United States)

Xia, Yongqiu; Li, Yuefei; Zhang, Xinyu; Yan, Xiaoyuan

2017-01-01

Nitrate (NO3-) pollution is a serious problem worldwide, particularly in countries with intensive agricultural and population activities. Previous studies have used δ15N-NO3- and δ18O-NO3- to determine the NO3- sources in rivers. However, this approach is subject to substantial uncertainties and limitations because of the numerous NO3- sources, the wide isotopic ranges, and the existing isotopic fractionations. In this study, we outline a combined procedure for improving the determination of NO3- sources in a paddy agriculture-urban gradient watershed in eastern China. First, the main sources of NO3- in the Qinhuai River were examined by the dual-isotope biplot approach, in which we narrowed the isotope ranges using site-specific isotopic results. Next, the bacterial groups and chemical properties of the river water were analyzed to verify these sources. Finally, we introduced a Bayesian model to apportion the spatiotemporal variations of the NO3- sources. Denitrification was first incorporated into the Bayesian model because denitrification plays an important role in the nitrogen pathway. The results showed that fertilizer contributed large amounts of NO3- to the surface water in traditional agricultural regions, whereas manure effluents were the dominant NO3- source in intensified agricultural regions, especially during the wet seasons. Sewage effluents were important in all three land uses and exhibited great differences between the dry season and the wet season. This combined analysis quantitatively delineates the proportion of NO3- sources from paddy agriculture to urban river water for both dry and wet seasons and incorporates isotopic fractionation and uncertainties in the source compositions.

Contributions of chemical exchange to T1ρ dispersion in a tissue model.

Science.gov (United States)

Cobb, Jared G; Xie, Jingping; Gore, John C

2011-12-01

Variations in T(1ρ) with locking-field strength (T(1ρ) dispersion) may be used to estimate proton exchange rates. We developed a novel approach utilizing the second derivative of the dispersion curve to measure exchange in a model system of cross-linked polyacrylamide gels. These gels were varied in relative composition of comonomers, increasing stiffness, and in pH, modifying exchange rates. Magnetic resonance images were recorded with a spin-locking sequence as described by Sepponen et al. These measurements were fit to a mono-exponential decay function yielding values for T(1ρ) at each locking-field measured. These values were then fit to a model by Chopra et al. for estimating exchange rates. For low stiffness gels, the calculated exchange values increased by a factor of 4 as pH increased, consistent with chemical exchange being the dominant contributor to T(1ρ) dispersion. Interestingly, calculated chemical exchange rates also increased with stiffness, likely due to modified side-chain exchange kinetics as the composition varied. This article demonstrates a new method to assess the structural and chemical effects on T(1ρ) relaxation dispersion with a suitable model. These phenomena may be exploited in an imaging context to emphasize the presence of nuclei of specific exchange rates, rather than chemical shifts. Copyright © 2011 Wiley Periodicals, Inc.

CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

Science.gov (United States)

Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-03-14

Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis and modelling of the energy consumption of chemical batch plants

Energy Technology Data Exchange (ETDEWEB)

Bieler, P.S.

2004-07-01

This report for the Swiss Federal Office of Energy (SFOE) describes two different approaches for the energy analysis and modelling of chemical batch plants. A top-down model consisting of a linear equation based on the specific energy consumption per ton of production output and the base consumption of the plant is postulated. The model is shown to be applicable to single and multi-product batches for batch plants with constant production mix and multi-purpose batch plants in which only similar chemicals are produced. For multipurpose batch plants with highly varying production processes and changing production mix, the top-down model produced inaccurate results. A bottom-up model is postulated for such plants. The results obtained are discussed that show that the electricity consumption for infrastructure equipment was significant and responsible for about 50% of total electricity consumption. The specific energy consumption for the different buildings was related to the degree of automation and the production processes. Analyses of the results of modelling are presented. More detailed analyses of the energy consumption of this apparatus group show that about 30 to 40% of steam energy is lost and thus a large potential for optimisation exists. Various potentials for making savings, ranging from elimination of reflux conditions to the development of a new heating/cooling-system for a generic batch reactor, are identified.

Overview of chemical modeling of nuclear waste glass dissolution

International Nuclear Information System (INIS)

Bourcier, W.L.

1991-02-01

Glass dissolution takes place through metal leaching and hydration of the glass surface accompanied by development of alternation layers of varying crystallinity. The reaction which controls the long-term glass dissolution rate appears to be surface layer dissolution. This reaction is reversible because the buildup of dissolved species in solution slows the dissolution rate due to a decreased dissolution affinity. Glass dissolution rates are therefore highly dependent on silica concentrations in solution because silica is the major component of the alteration layer. Chemical modeling of glass dissolution using reaction path computer codes has successfully been applied to short term experimental tests and used to predict long-term repository performance. Current problems and limitations of the models include a poorly defined long-term glass dissolution mechanism, the use of model parameters determined from the same experiments that the model is used to predict, and the lack of sufficient validation of key assumptions in the modeling approach. Work is in progress that addresses these issues. 41 refs., 7 figs., 2 tabs

Analysis of a Stochastic Chemical System Close to a SNIPER Bifurcation of Its Mean-Field Model

KAUST Repository

Erban, Radek

2009-01-01

A framework for the analysis of stochastic models of chemical systems for which the deterministic mean-field description is undergoing a saddle-node infinite period (SNIPER) bifurcation is presented. Such a bifurcation occurs, for example, in the modeling of cell-cycle regulation. It is shown that the stochastic system possesses oscillatory solutions even for parameter values for which the mean-field model does not oscillate. The dependence of the mean period of these oscillations on the parameters of the model (kinetic rate constants) and the size of the system (number of molecules present) are studied. Our approach is based on the chemical Fokker-Planck equation. To gain some insight into the advantages and disadvantages of the method, a simple one-dimensional chemical switch is first analyzed, and then the chemical SNIPER problem is studied in detail. First, results obtained by solving the Fokker-Planck equation numerically are presented. Then an asymptotic analysis of the Fokker-Planck equation is used to derive explicit formulae for the period of oscillation as a function of the rate constants and as a function of the system size. © 2009 Society for Industrial and Applied Mathematics.

Environmental Pollution, Toxicity Profile and Treatment Approaches for Tannery Wastewater and Its Chemical Pollutants.

Science.gov (United States)

Saxena, Gaurav; Chandra, Ram; Bharagava, Ram Naresh

Leather industries are key contributors in the economy of many developing countries, but unfortunately they are facing serious challenges from the public and governments due to the associated environmental pollution. There is a public outcry against the industry due to the discharge of potentially toxic wastewater having alkaline pH, dark brown colour, unpleasant odour, high biological and chemical oxygen demand, total dissolved solids and a mixture of organic and inorganic pollutants. Various environment protection agencies have prioritized several chemicals as hazardous and restricted their use in leather processing however; many of these chemicals are used and discharged in wastewater. Therefore, it is imperative to adequately treat/detoxify the tannery wastewater for environmental safety. This paper provides a detail review on the environmental pollution and toxicity profile of tannery wastewater and chemicals. Furthermore, the status and advances in the existing treatment approaches used for the treatment and/or detoxification of tannery wastewater at both laboratory and pilot/industrial scale have been reviewed. In addition, the emerging treatment approaches alone or in combination with biological treatment approaches have also been considered. Moreover, the limitations of existing and emerging treatment approaches have been summarized and potential areas for further investigations have been discussed. In addition, the clean technologies for waste minimization, control and management are also discussed. Finally, the international legislation scenario on discharge limits for tannery wastewater and chemicals has also been discussed country wise with discharge standards for pollution prevention due to tannery wastewater.

Human exposure assessment: Approaches for chemicals (REACH) and biocides (BPD)

NARCIS (Netherlands)

Hemmen, J.J. van; Gerritsen-Ebben, R.

2008-01-01

The approaches that are indicated in the various guidance documents for the assessment of human exposure for chemicals and biocides are summarised. This reflects the TNsG (Technical notes for Guidance) version 2: human exposure assessment for biocidal products (1) under the BPD (Biocidal Products

Modeling release of chemicals from multilayer materials into food

Directory of Open Access Journals (Sweden)

Huang Xiu-Ling

2016-01-01

Full Text Available The migration of chemicals from materials into food is predictable by various mathematical models. In this article, a general mathematical model is developed to quantify the release of chemicals through multilayer packaging films based on Fick's diffusion. The model is solved numerically to elucidate the effects of different diffusivity values of different layers, distribution of chemical between two adjacent layers and between material and food, mass transfer at the interface of material and food on the migration process.

Sensitivity of a Chemical Mass Balance model for PM2.5 to source profiles for differing styles of cooking

Science.gov (United States)

Abdullahi, K. L.; Delgado-Saborit, J. M.; Harrison, Roy M.

2018-04-01

Use of a Chemical Mass Balance model is one of the two most commonly used approaches to estimating atmospheric concentrations of cooking aerosol. Such models require the input of chemical profiles for each of the main sources contributing to particulate matter mass and there is appreciable evidence from the literature that not only the mass emission but also the chemical composition of particulate matter varies according to the food being prepared and the style of cooking. In this study, aerosol has been sampled in the laboratory from four different styles of cooking, i.e. Indian, Chinese, Western and African cooking. The chemical profiles of molecular markers have been quantified and are used individually within a Chemical Mass Balance model applied to air samples collected in a multi-ethnic area of Birmingham, UK. The model results give a source contribution estimate for cooking aerosol which is consistent with other comparable UK studies, but also shows a very low sensitivity of the model to the cooking aerosol profile utilised. A survey of local restaurants suggested a wide range of cooking styles taking place which may explain why no one profile gives an appreciably better fit in the CMB model.

QCD phase transition at real chemical potential with canonical approach

Energy Technology Data Exchange (ETDEWEB)

Nakamura, Atsushi [RCNP, Osaka University,Osaka, 567-0047 (Japan); Nishina Center, RIKEN,Wako, Saitama 351-0198 (Japan); School of Biomedicine, Far Eastern Federal University,Vladivostok, 690950 (Russian Federation); Oka, Shotaro [Institute of Theoretical Physics, Department of Physics, Rikkyo University,Toshima-ku, Tokyo 171-8501 (Japan); Taniguchi, Yusuke [Graduate School of Pure and Applied Sciences, University of Tsukuba,Tsukuba, Ibaraki 305-8571 (Japan)

2016-02-08

We study the finite density phase transition in the lattice QCD at real chemical potential. We adopt a canonical approach and the canonical partition function is constructed for N{sub f}=2 QCD. After derivation of the canonical partition function we calculate observables like the pressure, the quark number density, its second cumulant and the chiral condensate as a function of the real chemical potential. We covered a wide range of temperature region starting from the confining low to the deconfining high temperature; 0.65T{sub c}≤T≤3.62T{sub c}. We observe a possible signal of the deconfinement and the chiral restoration phase transition at real chemical potential below T{sub c} starting from the confining phase. We give also the convergence range of the fugacity expansion.

Chemical model reduction under uncertainty

KAUST Repository

Malpica Galassi, Riccardo; Valorani, Mauro; Najm, Habib N.; Safta, Cosmin; Khalil, Mohammad; Ciottoli, Pietro P.

2017-01-01

A general strategy for analysis and reduction of uncertain chemical kinetic models is presented, and its utility is illustrated in the context of ignition of hydrocarbon fuel–air mixtures. The strategy is based on a deterministic analysis

Identification of biased sectors in emission data using a combination of chemical transport model and receptor model

Science.gov (United States)

Uranishi, Katsushige; Ikemori, Fumikazu; Nakatsubo, Ryohei; Shimadera, Hikari; Kondo, Akira; Kikutani, Yuki; Asano, Katsuyoshi; Sugata, Seiji

2017-10-01

This study presented a comparison approach with multiple source apportionment methods to identify which sectors of emission data have large biases. The source apportionment methods for the comparison approach included both receptor and chemical transport models, which are widely used to quantify the impacts of emission sources on fine particulate matter of less than 2.5 μm in diameter (PM2.5). We used daily chemical component concentration data in the year 2013, including data for water-soluble ions, elements, and carbonaceous species of PM2.5 at 11 sites in the Kinki-Tokai district in Japan in order to apply the Positive Matrix Factorization (PMF) model for the source apportionment. Seven PMF factors of PM2.5 were identified with the temporal and spatial variation patterns and also retained features of the sites. These factors comprised two types of secondary sulfate, road transportation, heavy oil combustion by ships, biomass burning, secondary nitrate, and soil and industrial dust, accounting for 46%, 17%, 7%, 14%, 13%, and 3% of the PM2.5, respectively. The multiple-site data enabled a comprehensive identification of the PM2.5 sources. For the same period, source contributions were estimated by air quality simulations using the Community Multiscale Air Quality model (CMAQ) with the brute-force method (BFM) for four source categories. Both models provided consistent results for the following three of the four source categories: secondary sulfates, road transportation, and heavy oil combustion sources. For these three target categories, the models' agreement was supported by the small differences and high correlations between the CMAQ/BFM- and PMF-estimated source contributions to the concentrations of PM2.5, SO42-, and EC. In contrast, contributions of the biomass burning sources apportioned by CMAQ/BFM were much lower than and little correlated with those captured by the PMF model, indicating large uncertainties in the biomass burning emissions used in the

Bayesian molecular design with a chemical language model

Science.gov (United States)

Ikebata, Hisaki; Hongo, Kenta; Isomura, Tetsu; Maezono, Ryo; Yoshida, Ryo

2017-04-01

The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes' law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.

Effectiveness of Instruction Based on the Constructivist Approach on Understanding Chemical Equilibrium Concepts

Science.gov (United States)

Akkus, Huseyin; Kadayifci, Hakki; Atasoy, Basri; Geban, Omer

2003-01-01

The purpose of this study was to identify misconceptions concerning chemical equilibrium concepts and to investigate the effectiveness of instruction based on the constructivist approach over traditional instruction on 10th grade students' understanding of chemical equilibrium concepts. The subjects of this study consisted of 71 10th grade…

Review of laboratory-based terrestrial bioaccumulation assessment approaches for organic chemicals: Current status and future possibilities.

Science.gov (United States)

Hoke, Robert; Huggett, Duane; Brasfield, Sandra; Brown, Becky; Embry, Michelle; Fairbrother, Anne; Kivi, Michelle; Paumen, Miriam Leon; Prosser, Ryan; Salvito, Dan; Scroggins, Rick

2016-01-01

In the last decade, interest has been renewed in approaches for the assessment of the bioaccumulation potential of chemicals, principally driven by the need to evaluate large numbers of chemicals as part of new chemical legislation, while reducing vertebrate test organism use called for in animal welfare legislation. This renewed interest has inspired research activities and advances in bioaccumulation science for neutral organic chemicals in aquatic environments. In January 2013, ILSI Health and Environmental Sciences Institute convened experts to identify the state of the science and existing shortcomings in terrestrial bioaccumulation assessment of neutral organic chemicals. Potential modifications to existing laboratory methods were identified, including areas in which new laboratory approaches or test methods could be developed to address terrestrial bioaccumulation. The utility of "non-ecotoxicity" data (e.g., mammalian laboratory data) was also discussed. The highlights of the workshop discussions are presented along with potential modifications in laboratory approaches and new test guidelines that could be used for assessing the bioaccumulation of chemicals in terrestrial organisms. © 2015 SETAC.

Simplified fate modelling in respect to ecotoxicological and human toxicological characterisation of emissions of chemical compounds

DEFF Research Database (Denmark)

Birkved, Morten; Heijungs, Reinout

2011-01-01

The impact assessment of chemical compounds in Life Cycle Impact Assessment (LCIA) and Environmental Risk Assessment (ERA) requires a vast amount of data on the properties of the chemical compounds being assessed. The purpose of the present study is to explore statistical options for reduction...... of the data demand associated with characterisation of chemical emissions in LCIA and ERA.Based on a USEtox™ characterisation factor set consisting of 3,073 data records, multi-dimensional bilinear models for emission compartment specific fate characterisation of chemical emissions were derived by application...... the independent chemical input parameters from the minimum data set, needed for characterisation in USEtox™, according to general availability, importance and relevance for fate factor prediction.Each approach (63% and 75% of the minimum data set needed for characterisation in USEtox™) yielded 66 meta...

Critical reflections on the Chemical Leasing concept

NARCIS (Netherlands)

Lozano, Rodrigo; Carpenter, Angela; Lozano, Francisco J.

Chemical Leasing has been developed as a collaborative business model to complement the two main approaches (policy initiatives and scientific/ technological) used to foster green chemistry and sustainable chemistry. Chemical Leasing is based on using chemicals more efficiently, reducing waste, and

Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite

International Nuclear Information System (INIS)

Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.

2007-01-01

The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

Directory of Open Access Journals (Sweden)

Mihai V. Putz

2016-07-01

Full Text Available Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding and quantitative (for predicting mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD as the revived precursor for comparative molecular field analyses (CoMFA and comparative molecular similarity indices analysis (CoMSIA; all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy-methyl]-6-(phenylthiothymine congeners’ (HEPT ligands antiviral activity against Human Immunodeficiency Virus of first type (HIV-1 and new pharmacophores in treating severe genetic disorders (like depression and psychosis, respectively, all involving 3D pharmacophore interactions.

Development of a global 1-D chemically radiatively coupled model and an introduction to the development of a chemically coupled General Circulation Model

International Nuclear Information System (INIS)

Akiyoshi, H.

1997-01-01

A global one-dimensional, chemically and radiatively coupled model has been developed. The basic concept of the coupled model, definition of globally averaged zenith angles, the formulation of the model chemistry, radiation, the coupled processes, and profiles and diurnal variations of temperature and chemical species at a normal steady state are presented. Furthermore, a suddenly doubled CO 2 experiment and a Pinatubo aerosol increase experiment were performed with the model. The time scales of variations in ozone and temperature in the lower stratosphere of the coupled system in the doubled CO 2 experiment was long, due to a feedback process among ultra violet radiation, O(1D), NO y , NO x , and O 3 . From the Pinatubo aerosol experiment, a delay of maximum ozone decrease from the maximum aerosol loading is shown and discussed. Developments of 3-D chemical models with coupled processes are briefly described, and the ozone distribution from the first version of the 3-D model are presented. Chemical model development in National Institute for Environmental Studies (NIES) are briefly described. (author)

Real-time nonlinear feedback control of pattern formation in (bio)chemical reaction-diffusion processes: a model study.

Science.gov (United States)

Brandt-Pollmann, U; Lebiedz, D; Diehl, M; Sager, S; Schlöder, J

2005-09-01

Theoretical and experimental studies related to manipulation of pattern formation in self-organizing reaction-diffusion processes by appropriate control stimuli become increasingly important both in chemical engineering and cellular biochemistry. In a model study, we demonstrate here exemplarily the application of an efficient nonlinear model predictive control (NMPC) algorithm to real-time optimal feedback control of pattern formation in a bacterial chemotaxis system modeled by nonlinear partial differential equations. The corresponding drift-diffusion model type is representative for many (bio)chemical systems involving nonlinear reaction dynamics and nonlinear diffusion. We show how the computed optimal feedback control strategy exploits the system inherent physical property of wave propagation to achieve desired control aims. We discuss various applications of our approach to optimal control of spatiotemporal dynamics.

Perspective: Reaches of chemical physics in biology

Science.gov (United States)

Gruebele, Martin; Thirumalai, D.

2013-01-01

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry. PMID:24089712

Perspective: Reaches of chemical physics in biology.

Science.gov (United States)

Gruebele, Martin; Thirumalai, D

2013-09-28

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry.

Thai students' mental model of chemical bonding

Science.gov (United States)

Sarawan, Supawadee; Yuenyong, Chokchai

2018-01-01

This Research was finding the viewing about concept of chemical bonding is fundamental to subsequent learning of various other topics related to this concept in chemistry. Any conceptions about atomic structures that students have will be shown their further learning. The purpose of this study is to interviews conceptions held by high school chemistry students about metallic bonding and to reveal mental model of atomic structures show according to the educational level. With this aim, the questionnaire prepared making use of the literature and administered for analysis about mental model of chemical bonding. It was determined from the analysis of answers of questionnaire the 10th grade, 11th grade and 12th grade students. Finally, each was shown prompts in the form of focus cards derived from curriculum material that showed ways in which the bonding in specific metallic substances had been depicted. Students' responses revealed that learners across all three levels prefer simple, realistic mental models for metallic bonding and reveal to chemical bonding.

The terrorist threat nuclear, radiological, biological, chemical - a medical approach

International Nuclear Information System (INIS)

Revel, M.C. de; Gourmelon, M.C.S.; Vidal, P.C.; Renaudeau, P.C.S.

2005-01-01

Since September 11, 2001, the fear of a large scale nuclear, biological and/or chemical terrorism is taken again into consideration at the highest level of national policies of risk prevention. The advent of international terrorism implies a cooperation between the military defense and the civil defense. The nuclear, radiological, biological and chemical (NRBC) experts of the health service of army and of civil defense will have to work together in case of major terror attack. This book presents this cooperation between civil and military experts in the NRBC domain: risk analysis, national defense plans, crisis management, syndromes and treatments. The different aspects linked with the use of nuclear, biological and chemical weapons are analyzed by the best experts from French medical and research institutes. All topics of each NRBC domain are approached: historical, basic, diagnostic, therapeutic and preventive. (J.S.)

Fluorine in the solar neighborhood: Chemical evolution models

Science.gov (United States)

Spitoni, E.; Matteucci, F.; Jönsson, H.; Ryde, N.; Romano, D.

2018-04-01

Context. In light of new observational data related to fluorine abundances in solar neighborhood stars, we present chemical evolution models testing various fluorine nucleosynthesis prescriptions with the aim to best fit those new data. Aim. We consider chemical evolution models in the solar neighborhood testing various nucleosynthesis prescriptions for fluorine production with the aim of reproducing the observed abundance ratios [F/O] versus [O/H] and [F/Fe] versus [Fe/H]. We study in detail the effects of various stellar yields on fluorine production. Methods: We adopted two chemical evolution models: the classical two-infall model, which follows the chemical evolution of halo-thick disk and thin disk phases; and the one-infall model, which is designed only for thin disk evolution. We tested the effects on the predicted fluorine abundance ratios of various nucleosynthesis yield sources, that is, asymptotic giant branch (AGB) stars, Wolf-Rayet (W-R) stars, Type II and Type Ia supernovae, and novae. Results: The fluorine production is dominated by AGB stars but the W-R stars are required to reproduce the trend of the observed data in the solar neighborhood with our chemical evolution models. In particular, the best model both for the two-infall and one-infall cases requires an increase by a factor of 2 of the W-R yields. We also show that the novae, even if their yields are still uncertain, could help to better reproduce the secondary behavior of F in the [F/O] versus [O/H] relation. Conclusions: The inclusion of the fluorine production by W-R stars seems to be essential to reproduce the new observed ratio [F/O] versus [O/H] in the solar neighborhood. Moreover, the inclusion of novae helps to reproduce the observed fluorine secondary behavior substantially.

Thermal-Chemical Model Of Subduction: Results And Tests

Science.gov (United States)

Gorczyk, W.; Gerya, T. V.; Connolly, J. A.; Yuen, D. A.; Rudolph, M.

2005-12-01

Seismic structures with strong positive and negative velocity anomalies in the mantle wedge above subduction zones have been interpreted as thermally and/or chemically induced phenomena. We have developed a thermal-chemical model of subduction, which constrains the dynamics of seismic velocity structure beneath volcanic arcs. Our simulations have been calculated over a finite-difference grid with (201×101) to (201×401) regularly spaced Eulerian points, using 0.5 million to 10 billion markers. The model couples numerical thermo-mechanical solution with Gibbs energy minimization to investigate the dynamic behavior of partially molten upwellings from slabs (cold plumes) and structures associated with their development. The model demonstrates two chemically distinct types of plumes (mixed and unmixed), and various rigid body rotation phenomena in the wedge (subduction wheel, fore-arc spin, wedge pin-ball). These thermal-chemical features strongly perturb seismic structure. Their occurrence is dependent on the age of subducting slab and the rate of subduction.The model has been validated through a series of test cases and its results are consistent with a variety of geological and geophysical data. In contrast to models that attribute a purely thermal origin for mantle wedge seismic anomalies, the thermal-chemical model is able to simulate the strong variations of seismic velocity existing beneath volcanic arcs which are associated with development of cold plumes. In particular, molten regions that form beneath volcanic arcs as a consequence of vigorous cold wet plumes are manifest by > 20% variations in the local Poisson ratio, as compared to variations of ~ 2% expected as a consequence of temperature variation within the mantle wedge.

AMAZON RAINFOREST COSMETICS: CHEMICAL APPROACH FOR QUALITY CONTROL

Directory of Open Access Journals (Sweden)

Mariko Funasaki

2016-02-01

Full Text Available The market for natural cosmetics featuring ingredients derived from Amazon natural resources is growing worldwide. However, there is neither enough scientific basis nor quality control of these ingredients. This paper is an account of the chemical constituents and their biological activities of fourteen Amazonian species used in cosmetic industry, including açaí (Euterpe oleracea, andiroba (Carapa guianensis, bacuri (Platonia insignis, Brazil nut (Bertholletia excelsa, buriti (Mauritia vinifera or M. flexuosa, cumaru (Dipteryx odorata, cupuaçu (Theobroma grandiflorum, guarana (Paullinia cupana, mulateiro (Calycophyllum spruceanum, murumuru (Astrocaryum murumuru, patawa (Oenocarpus bataua or Jessenia bataua, pracaxi (Pentaclethra macroloba, rosewood (Aniba rosaeodora, and ucuuba (Virola sebifera. Based on the reviewed articles, we selected chemical markers for the quality control purpose and evaluated analytical methods. Even though chromatographic and spectroscopic methods are major analytical techniques in the studies of these species, molecular approaches will also be important as used in food and medicine traceability. Only a little phytochemical study is available about most of the Amazonian species and some species such as açaí and andiroba have many reports on chemical constituents, but studies on biological activities of isolated compounds and sampling with geographical variation are limited.

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model.

Science.gov (United States)

Kroonblawd, Matthew P; Pietrucci, Fabio; Saitta, Antonino Marco; Goldman, Nir

2018-04-10

We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol -1 .

Progress in Chemical Kinetic Modeling for Surrogate Fuels

Energy Technology Data Exchange (ETDEWEB)

Pitz, W J; Westbrook, C K; Herbinet, O; Silke, E J

2008-06-06

Gasoline, diesel, and other alternative transportation fuels contain hundreds to thousands of compounds. It is currently not possible to represent all these compounds in detailed chemical kinetic models. Instead, these fuels are represented by surrogate fuel models which contain a limited number of representative compounds. We have been extending the list of compounds for detailed chemical models that are available for use in fuel surrogate models. Detailed models for components with larger and more complicated fuel molecular structures are now available. These advancements are allowing a more accurate representation of practical and alternative fuels. We have developed detailed chemical kinetic models for fuels with higher molecular weight fuel molecules such as n-hexadecane (C16). Also, we can consider more complicated fuel molecular structures like cyclic alkanes and aromatics that are found in practical fuels. For alternative fuels, the capability to model large biodiesel fuels that have ester structures is becoming available. These newly addressed cyclic and ester structures in fuels profoundly affect the reaction rate of the fuel predicted by the model. Finally, these surrogate fuel models contain large numbers of species and reactions and must be reduced for use in multi-dimensional models for spark-ignition, HCCI and diesel engines.

Cumulus parameterizations in chemical transport models

Science.gov (United States)

Mahowald, Natalie M.; Rasch, Philip J.; Prinn, Ronald G.

1995-12-01

Global three-dimensional chemical transport models (CTMs) are valuable tools for studying processes controlling the distribution of trace constituents in the atmosphere. A major uncertainty in these models is the subgrid-scale parametrization of transport by cumulus convection. This study seeks to define the range of behavior of moist convective schemes and point toward more reliable formulations for inclusion in chemical transport models. The emphasis is on deriving convective transport from meteorological data sets (such as those from the forecast centers) which do not routinely include convective mass fluxes. Seven moist convective parameterizations are compared in a column model to examine the sensitivity of the vertical profile of trace gases to the parameterization used in a global chemical transport model. The moist convective schemes examined are the Emanuel scheme [Emanuel, 1991], the Feichter-Crutzen scheme [Feichter and Crutzen, 1990], the inverse thermodynamic scheme (described in this paper), two versions of a scheme suggested by Hack [Hack, 1994], and two versions of a scheme suggested by Tiedtke (one following the formulation used in the ECMWF (European Centre for Medium-Range Weather Forecasting) and ECHAM3 (European Centre and Hamburg Max-Planck-Institut) models [Tiedtke, 1989], and one formulated as in the TM2 (Transport Model-2) model (M. Heimann, personal communication, 1992). These convective schemes vary in the closure used to derive the mass fluxes, as well as the cloud model formulation, giving a broad range of results. In addition, two boundary layer schemes are compared: a state-of-the-art nonlocal boundary layer scheme [Holtslag and Boville, 1993] and a simple adiabatic mixing scheme described in this paper. Three tests are used to compare the moist convective schemes against observations. Although the tests conducted here cannot conclusively show that one parameterization is better than the others, the tests are a good measure of the

An approach to quantitate and control the mutagenic hazards of environmental chemical and radioactive pollutants

International Nuclear Information System (INIS)

Murthy, M.S.S.

1977-01-01

Human population, both at the occupational and non-occupational levels, is exposed to the environment polluted by man-made chemicals and radiation sources. The parameters required for quantitating mutagenic hazards of any agent are listed and it has been pointed out that though sufficient information of this nature is available in the case of radiations, it is almost impossible to collect similar information for chemical substances due to their number running into astronomical figures. A short-cut approach, therefore, is suggested to quantitate and control the mutagenic hazards of these pollutants. It is to express the mutagenic hazards of a chemical substance in terms of equivalent radiation units. The unit proposed for this purpose is called as Rem-Equivalent Chemical (REC). Total mutagenic burden to the society should take account of exposure from both chemicals and radiations. Advantages and limitation of this approach are discussed. (M.G.B.)

Molecular finite-size effects in stochastic models of equilibrium chemical systems.

Science.gov (United States)

Cianci, Claudia; Smith, Stephen; Grima, Ramon

2016-02-28

The reaction-diffusion master equation (RDME) is a standard modelling approach for understanding stochastic and spatial chemical kinetics. An inherent assumption is that molecules are point-like. Here, we introduce the excluded volume reaction-diffusion master equation (vRDME) which takes into account volume exclusion effects on stochastic kinetics due to a finite molecular radius. We obtain an exact closed form solution of the RDME and of the vRDME for a general chemical system in equilibrium conditions. The difference between the two solutions increases with the ratio of molecular diameter to the compartment length scale. We show that an increase in the fraction of excluded space can (i) lead to deviations from the classical inverse square root law for the noise-strength, (ii) flip the skewness of the probability distribution from right to left-skewed, (iii) shift the equilibrium of bimolecular reactions so that more product molecules are formed, and (iv) strongly modulate the Fano factors and coefficients of variation. These volume exclusion effects are found to be particularly pronounced for chemical species not involved in chemical conservation laws. Finally, we show that statistics obtained using the vRDME are in good agreement with those obtained from Brownian dynamics with excluded volume interactions.

A Gibbs Energy Minimization Approach for Modeling of Chemical Reactions in a Basic Oxygen Furnace

Science.gov (United States)

Kruskopf, Ari; Visuri, Ville-Valtteri

2017-12-01

In modern steelmaking, the decarburization of hot metal is converted into steel primarily in converter processes, such as the basic oxygen furnace. The objective of this work was to develop a new mathematical model for top blown steel converter, which accounts for the complex reaction equilibria in the impact zone, also known as the hot spot, as well as the associated mass and heat transport. An in-house computer code of the model has been developed in Matlab. The main assumption of the model is that all reactions take place in a specified reaction zone. The mass transfer between the reaction volume, bulk slag, and metal determine the reaction rates for the species. The thermodynamic equilibrium is calculated using the partitioning of Gibbs energy (PGE) method. The activity model for the liquid metal is the unified interaction parameter model and for the liquid slag the modified quasichemical model (MQM). The MQM was validated by calculating iso-activity lines for the liquid slag components. The PGE method together with the MQM was validated by calculating liquidus lines for solid components. The results were compared with measurements from literature. The full chemical reaction model was validated by comparing the metal and slag compositions to measurements from industrial scale converter. The predictions were found to be in good agreement with the measured values. Furthermore, the accuracy of the model was found to compare favorably with the models proposed in the literature. The real-time capability of the proposed model was confirmed in test calculations.

Unicorns in the world of chemical bonding models.

Science.gov (United States)

Frenking, Gernot; Krapp, Andreas

2007-01-15

The appearance and the significance of heuristically developed bonding models are compared with the phenomenon of unicorns in mythical saga. It is argued that classical bonding models played an essential role for the development of the chemical science providing the language which is spoken in the territory of chemistry. The advent and the further development of quantum chemistry demands some restrictions and boundary conditions for classical chemical bonding models, which will continue to be integral parts of chemistry. Copyright (c) 2006 Wiley Periodicals, Inc.

Assessment of the eye irritation potential of chemicals: A comparison study between two test methods based on human 3D hemi-cornea models.

Science.gov (United States)

Tandon, R; Bartok, M; Zorn-Kruppa, M; Brandner, J M; Gabel, D; Engelke, M

2015-12-25

We have recently developed two hemi-cornea models (Bartok et al., Toxicol in Vitro 29, 72, 2015; Zorn-Kruppa et al. PLoS One 9, e114181, 2014), which allow the correct prediction of eye irritation potential of chemicals according to the United Nations globally harmonized system of classification and labeling of chemicals (UN GHS). Both models comprise a multilayered epithelium and a stroma with embedded keratocytes in a collagenous matrix. These two models were compared, using a set of fourteen test chemicals. Their effects after 10 and 60 minutes (min) exposure were assessed from the quantification of cell viability using the MTT reduction assay. The first approach separately quantifies the damage inflicted to the epithelium and the stroma. The second approach quantifies the depth of injury by recording cell death as a function of depth. The classification obtained by the two models was compared to the Draize rabbit eye test and an ex vivo model using rabbit cornea (Jester et al. Toxicol in Vitro. 24, 597-604, 2010). With a 60 min exposure, both of our models are able to clearly differentiate UN GHS Category 1 and UN GHS Category 2 test chemicals. Copyright © 2015 Elsevier Ltd. All rights reserved.

X-rays in protoplanetary disks : Their impact on the thermal and chemical structure, a grid of models

NARCIS (Netherlands)

Aresu, G.; Kamp, I.; Meijerink, R.; Woitke, P.; Thi, W. F.; Spaans, M.C.

X-rays impact protoplanetary disks hydrostatic, thermal and chemical structure. The range of efficiency of X-rays is explored using a grid modelling approach: different parameters affects the structure of the disk, this determines different contribution of the X-ray radiation to the chemistry and

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

Science.gov (United States)

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

Estimating chemical footprint: Contamination with mercury and its compounds

DEFF Research Database (Denmark)

Tarasova, Natalia; Makarova, Anna; Fantke, Peter

2018-01-01

-SETAC scientific consensus model USEtox, which is recommended for and widely applied in life cycle impact assessment. Our approach was tested using the example of mercury, which has been shown to be a hazardous pollutant at regional and global scales. Results show that the main contribution to the overall chemical......Chemical pollution is a problem of global importance. However, there are currently no agreed approaches for integrated environmental impact assessment (EIA) of chemical effects at global scale. We present a new systems-based approach to EIA of chemicals. Our methodology considers propagation...... of chemical pollutants in the environment, in conjunction with the approach followed in the Russian regulatory system. To estimate chemical footprints related to environmental contamination by potentially toxic substances, measured environmental concentrations were combined with results from the UNEP...

Exploring the role of quantum chemical descriptors in modeling acute toxicity of diverse chemicals to Daphnia magna.

Science.gov (United States)

Reenu; Vikas

2015-09-01

Various quantum-mechanically computed molecular and thermodynamic descriptors along with physico-chemical, electrostatic and topological descriptors are compared while developing quantitative structure-activity relationships (QSARs) for the acute toxicity of 252 diverse organic chemicals towards Daphnia magna. QSAR models based on the quantum-chemical descriptors, computed with routinely employed advanced semi-empirical and ab-initio methods, along with the electron-correlation contribution (CORR) of the descriptors, are analyzed for the external predictivity of the acute toxicity. The models with reliable internal stability and external predictivity are found to be based on the HOMO energy along with the physico-chemical, electrostatic and topological descriptors. Besides this, the total energy and electron-correlation energy are also observed as highly reliable descriptors, suggesting that the intra-molecular interactions between the electrons play an important role in the origin of the acute toxicity, which is in fact an unexplored phenomenon. The models based on quantum-chemical descriptors such as chemical hardness, absolute electronegativity, standard Gibbs free energy and enthalpy are also observed to be reliable. A comparison of the robust models based on the quantum-chemical descriptors computed with various quantum-mechanical methods suggests that the advanced semi-empirical methods such as PM7 can be more reliable than the ab-initio methods which are computationally more expensive. Copyright © 2015 Elsevier Inc. All rights reserved.

Durability of cement-based materials: modeling of the influence of physical and chemical equilibria on the microstructure and the residual mechanical properties

International Nuclear Information System (INIS)

Guillon, E.

2004-09-01

A large part of mechanical and durability characteristics of cement-based materials comes from the performances of the hydrated cement, cohesive matrix surrounding the granular skeleton. Experimental studies, in situ or in laboratory, associated to models, have notably enhanced knowledge on the cement material and led to adapted formulations to specific applications or particularly aggressive environments. Nevertheless, these models, developed for precise cases, do not permit to specifically conclude for other experimental conclusions. To extend its applicability domain, we propose a new evolutive approach, based on reactive transport expressed at the microstructure scale of the cement. In a general point of view, the evolution of the solid compounds of the cement matrix, by dissolutions or precipitations, during chemical aggressions can be related to the pore solution evolution, and this one relied to the ionic exchanges with the external environment. By the utilization of a geochemical code associated to a thermodynamical database and coupled to a 3D transport model, this approach authorizes the study of all aggressive solution. The approach has been validated by the comparison of experimental observations to simulated degradations for three different environments (pure water, mineralized water, seawater) and on three different materials (CEM I Portland cement with 0.25, 0.4 and 0.5 water-to cement ratio). The microstructural approach permits also to have access to mechanical properties evolutions. During chemical aggressions, the cement matrix evolution is traduced in a microstructure evolution. This one is represented from 3D images similarly to the models developed at NIST (National Institute of Standards and Technology). A new finite-element model, validated on previous tests or models, evaluates the stiffness of the cement paste, using as a mesh these microstructures. Our approach identifies and quantifies the major influence of porosity and its spatial

Simulating adsorption of U(VI) under transient groundwater flow and hydrochemistry: Physical versus chemical nonequilibrium model

Science.gov (United States)

Greskowiak, J.; Hay, M.B.; Prommer, H.; Liu, C.; Post, V.E.A.; Ma, R.; Davis, J.A.; Zheng, C.; Zachara, J.M.

2011-01-01

Coupled intragrain diffusional mass transfer and nonlinear surface complexation processes play an important role in the transport behavior of U(VI) in contaminated aquifers. Two alternative model approaches for simulating these coupled processes were analyzed and compared: (1) the physical nonequilibrium approach that explicitly accounts for aqueous speciation and instantaneous surface complexation reactions in the intragrain regions and approximates the diffusive mass exchange between the immobile intragrain pore water and the advective pore water as multirate first-order mass transfer and (2) the chemical nonequilibrium approach that approximates the diffusion-limited intragrain surface complexation reactions by a set of multiple first-order surface complexation reaction kinetics, thereby eliminating the explicit treatment of aqueous speciation in the intragrain pore water. A model comparison has been carried out for column and field scale scenarios, representing the highly transient hydrological and geochemical conditions in the U(VI)-contaminated aquifer at the Hanford 300A site, Washington, USA. It was found that the response of U(VI) mass transfer behavior to hydrogeochemically induced changes in U(VI) adsorption strength was more pronounced in the physical than in the chemical nonequilibrium model. The magnitude of the differences in model behavior depended particularly on the degree of disequilibrium between the advective and immobile phase U(VI) concentrations. While a clear difference in U(VI) transport behavior between the two models was noticeable for the column-scale scenarios, only minor differences were found for the Hanford 300A field scale scenarios, where the model-generated disequilibrium conditions were less pronounced as a result of frequent groundwater flow reversals. Copyright 2011 by the American Geophysical Union.

Systematic Approach to Calculate the Concentration of Chemical Species in Multi-Equilibrium Problems

Science.gov (United States)

Baeza-Baeza, Juan Jose; Garcia-Alvarez-Coque, Maria Celia

2011-01-01

A general systematic approach is proposed for the numerical calculation of multi-equilibrium problems. The approach involves several steps: (i) the establishment of balances involving the chemical species in solution (e.g., mass balances, charge balance, and stoichiometric balance for the reaction products), (ii) the selection of the unknowns (the…

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

Science.gov (United States)

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

Science.gov (United States)

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

Computer-Aided Construction of Chemical Kinetic Models

Energy Technology Data Exchange (ETDEWEB)

Green, William H. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

2014-12-31

The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriate refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.

A network dynamics approach to chemical reaction networks

Science.gov (United States)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

Modelling Chemical Equilibrium Partitioning with the GEMS-PSI Code

Energy Technology Data Exchange (ETDEWEB)

Kulik, D.; Berner, U.; Curti, E

2004-03-01

Sorption, co-precipitation and re-crystallisation are important retention processes for dissolved contaminants (radionuclides) migrating through the sub-surface. The retention of elements is usually measured by empirical partition coefficients (Kd), which vary in response to many factors: temperature, solid/liquid ratio, total contaminant loading, water composition, host-mineral composition, etc. The Kd values can be predicted for in-situ conditions from thermodynamic modelling of solid solution, aqueous solution or sorption equilibria, provided that stoichiometry, thermodynamic stability and mixing properties of the pure components are known (Example 1). Unknown thermodynamic properties can be retrieved from experimental Kd values using inverse modelling techniques (Example 2). An efficient, advanced tool for performing both tasks is the Gibbs Energy Minimization (GEM) approach, implemented in the user-friendly GEM-Selector (GEMS) program package, which includes the Nagra-PSI chemical thermodynamic database. The package is being further developed at PSI and used extensively in studies relating to nuclear waste disposal. (author)

Modelling Chemical Equilibrium Partitioning with the GEMS-PSI Code

International Nuclear Information System (INIS)

Kulik, D.; Berner, U.; Curti, E.

2004-01-01

Sorption, co-precipitation and re-crystallisation are important retention processes for dissolved contaminants (radionuclides) migrating through the sub-surface. The retention of elements is usually measured by empirical partition coefficients (Kd), which vary in response to many factors: temperature, solid/liquid ratio, total contaminant loading, water composition, host-mineral composition, etc. The Kd values can be predicted for in-situ conditions from thermodynamic modelling of solid solution, aqueous solution or sorption equilibria, provided that stoichiometry, thermodynamic stability and mixing properties of the pure components are known (Example 1). Unknown thermodynamic properties can be retrieved from experimental Kd values using inverse modelling techniques (Example 2). An efficient, advanced tool for performing both tasks is the Gibbs Energy Minimization (GEM) approach, implemented in the user-friendly GEM-Selector (GEMS) program package, which includes the Nagra-PSI chemical thermodynamic database. The package is being further developed at PSI and used extensively in studies relating to nuclear waste disposal. (author)

EDF's approach to determine specifications for nuclear power plant bulk chemicals

International Nuclear Information System (INIS)

Basile, Alix; Dijoux, Michel; Le-Calvar, Marc; Gressier, Frederic; Mole, Didier

2012-09-01

Chemical impurities in the primary, secondary and auxiliary nuclear power plants circuits generate risks of corrosion of the fuel cladding, steel and nickel based alloys. The PMUC (Products and Materials Used in plants) organization established by EDF intends to limit this risk by specifying maximum levels of impurities in products and materials used for the operation and maintenance of Nuclear Power Plants (NPPs). Bulk chemicals specifications, applied on primary and secondary circuit chemicals and hydrogen and nitrogen gases, are particularly important to prevent chemical species to be involved in the corrosion of the NPPs materials. The application of EDF specifications should lead to reasonably exclude any risk of degradation of the first and second containment barriers and auxiliary circuits Important to Safety (IPS) by limiting the concentrations of chlorides, fluorides, sulfates... The risk of metal embrittlement by elements with low melting point (mercury, lead...) is also included. For the primary circuit, the specifications intend to exclude the risk of activation of impurities introduced by the bulk chemicals. For the first containment barrier, to reduce the risk of deposits like zeolites, PMUC products specifications set limit values for calcium, magnesium, aluminum and silica. EDF's approach for establishing specifications for bulk chemicals is taking also into account the capacity of industrial production, as well as costs, limitations of analytical control methods (detection limits) and environmental releases issues. This paper aims to explain EDF's approach relative to specifications of impurities in bulk chemicals. Also presented are the various parameters taken into account to determine the maximum pollution levels in the chemicals, the theoretical hypothesis to set the specifications and the calculation method used to verify that the specifications are suitable. (authors)

Evaluation of semi-generic PBTK modeling for emergency risk assessment after acute inhalation exposure to volatile hazardous chemicals.

Science.gov (United States)

Olie, J Daniël N; Bessems, Jos G; Clewell, Harvey J; Meulenbelt, Jan; Hunault, Claudine C

2015-08-01

Physiologically Based Toxicokinetic Models (PBTK) may facilitate emergency risk assessment after chemical incidents with inhalation exposure, but they are rarely used due to their relative complexity and skill requirements. We aimed to tackle this problem by evaluating a semi-generic PBTK model built in MS Excel for nine chemicals that are widely-used and often released in a chemical incident. The semi-generic PBTK model was used to predict blood concentration-time curves using inhalation exposure scenarios from human volunteer studies, case reports and hypothetical exposures at Emergency Response Planning Guideline, Level 3 (ERPG-3) levels.(2) Predictions using this model were compared with measured blood concentrations from volunteer studies or case reports, as well as blood concentrations predicted by chemical-specific models. The performances of the semi-generic model were evaluated on biological rationale, accuracy, and ease of use and range of application. Our results indicate that the semi-generic model can be easily used to predict blood levels for eight out of nine parent chemicals (dichloromethane, benzene, xylene, styrene, toluene, isopropanol trichloroethylene and tetrachloroethylene). However, for methanol, 2-propanol and dichloromethane the semi-generic model could not cope with the endogenous production of methanol and of acetone (being a metabolite of 2-propanol) nor could it simulate the formation of HbCO, which is one of the toxic end-points of dichloromethane. The model is easy and intuitive to use by people who are not so familiar with toxicokinetic models. A semi-generic PBTK modeling approach can be used as a 'quick-and-dirty' method to get a crude estimate of the exposure dose. Copyright © 2015 Elsevier Ltd. All rights reserved.

Environmental fate and transport of chemical signatures from buried landmines -- Screening model formulation and initial simulations

Energy Technology Data Exchange (ETDEWEB)

Phelan, J.M.; Webb, S.W.

1997-06-01

The fate and transport of chemical signature molecules that emanate from buried landmines is strongly influenced by physical chemical properties and by environmental conditions of the specific chemical compounds. Published data have been evaluated as the input parameters that are used in the simulation of the fate and transport processes. A one-dimensional model developed for screening agricultural pesticides was modified and used to simulate the appearance of a surface flux above a buried landmine, estimate the subsurface total concentration, and show the phase specific concentrations at the ground surface. The physical chemical properties of TNT cause a majority of the mass released to the soil system to be bound to the solid phase soil particles. The majority of the transport occurs in the liquid phase with diffusion and evaporation driven advection of soil water as the primary mechanisms for the flux to the ground surface. The simulations provided herein should only be used for initial conceptual designs of chemical pre-concentration subsystems or complete detection systems. The physical processes modeled required necessary simplifying assumptions to allow for analytical solutions. Emerging numerical simulation tools will soon be available that should provide more realistic estimates that can be used to predict the success of landmine chemical detection surveys based on knowledge of the chemical and soil properties, and environmental conditions where the mines are buried. Additional measurements of the chemical properties in soils are also needed before a fully predictive approach can be confidently applied.

Modeling Chemical Reactions by QM/MM Calculations: The Case of the Tautomerization in Fireflies Bioluminescent Systems.

Science.gov (United States)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-01-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modeling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Modelling chemical reactions by QM/MM calculations: the case of the tautomerization in fireflies bioluminescent systems

Science.gov (United States)

Berraud-Pache, Romain; Garcia-Iriepa, Cristina; Navizet, Isabelle

2018-04-01

In less than half a century, the hybrid QM/MM method has become one of the most used technique to model molecules embedded in a complex environment. A well-known application of the QM/MM method is for biological systems. Nowadays, one can understand how enzymatic reactions work or compute spectroscopic properties, like the wavelength of emission. Here, we have tackled the issue of modelling chemical reactions inside proteins. We have studied a bioluminescent system, fireflies, and deciphered if a keto-enol tautomerization is possible inside the protein. The two tautomers are candidates to be the emissive molecule of the bioluminescence but no outcome has been reached. One hypothesis is to consider a possible keto-enol tautomerization to treat this issue, as it has been already observed in water. A joint approach combining extensive MD simulations as well as computation of key intermediates like TS using QM/MM calculations is presented in this publication. We also emphasize the procedure and difficulties met during this approach in order to give a guide for this kind of chemical reactions using QM/MM methods.

Multi-scenario modelling of uncertainty in stochastic chemical systems

International Nuclear Information System (INIS)

Evans, R. David; Ricardez-Sandoval, Luis A.

2014-01-01

Uncertainty analysis has not been well studied at the molecular scale, despite extensive knowledge of uncertainty in macroscale systems. The ability to predict the effect of uncertainty allows for robust control of small scale systems such as nanoreactors, surface reactions, and gene toggle switches. However, it is difficult to model uncertainty in such chemical systems as they are stochastic in nature, and require a large computational cost. To address this issue, a new model of uncertainty propagation in stochastic chemical systems, based on the Chemical Master Equation, is proposed in the present study. The uncertain solution is approximated by a composite state comprised of the averaged effect of samples from the uncertain parameter distributions. This model is then used to study the effect of uncertainty on an isomerization system and a two gene regulation network called a repressilator. The results of this model show that uncertainty in stochastic systems is dependent on both the uncertain distribution, and the system under investigation. -- Highlights: •A method to model uncertainty on stochastic systems was developed. •The method is based on the Chemical Master Equation. •Uncertainty in an isomerization reaction and a gene regulation network was modelled. •Effects were significant and dependent on the uncertain input and reaction system. •The model was computationally more efficient than Kinetic Monte Carlo

Finite state projection based bounds to compare chemical master equation models using single-cell data

Energy Technology Data Exchange (ETDEWEB)

Fox, Zachary [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Neuert, Gregor [Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232 (United States); Department of Pharmacology, School of Medicine, Vanderbilt University, Nashville, Tennessee 37232 (United States); Department of Biomedical Engineering, Vanderbilt University School of Engineering, Nashville, Tennessee 37232 (United States); Munsky, Brian [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States)

2016-08-21

Emerging techniques now allow for precise quantification of distributions of biological molecules in single cells. These rapidly advancing experimental methods have created a need for more rigorous and efficient modeling tools. Here, we derive new bounds on the likelihood that observations of single-cell, single-molecule responses come from a discrete stochastic model, posed in the form of the chemical master equation. These strict upper and lower bounds are based on a finite state projection approach, and they converge monotonically to the exact likelihood value. These bounds allow one to discriminate rigorously between models and with a minimum level of computational effort. In practice, these bounds can be incorporated into stochastic model identification and parameter inference routines, which improve the accuracy and efficiency of endeavors to analyze and predict single-cell behavior. We demonstrate the applicability of our approach using simulated data for three example models as well as for experimental measurements of a time-varying stochastic transcriptional response in yeast.

Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter

KAUST Repository

Gharamti, M. E.; Kadoura, A.; Valstar, J.; Sun, S.; Hoteit, Ibrahim

2014-01-01

Isothermal compositional flow models require coupling transient compressible flows and advective transport systems of various chemical species in subsurface porous media. Building such numerical models is quite challenging and may be subject to many sources of uncertainties because of possible incomplete representation of some geological parameters that characterize the system's processes. Advanced data assimilation methods, such as the ensemble Kalman filter (EnKF), can be used to calibrate these models by incorporating available data. In this work, we consider the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components. We carry out state-parameter estimation experiments using joint and dual updating schemes in the context of the EnKF with a two-dimensional single-phase compositional flow model (CFM). Quantitative and statistical analyses are performed to evaluate and compare the performance of the assimilation schemes. Our results indicate that including chemical composition data significantly enhances the accuracy of the permeability estimates. In addition, composition data provide more information to estimate system states and parameters than do standard pressure data. The dual state-parameter estimation scheme provides about 10% more accurate permeability estimates on average than the joint scheme when implemented with the same ensemble members, at the cost of twice more forward model integrations. At similar computational cost, the dual approach becomes only beneficial after using large enough ensembles.

Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter

KAUST Repository

Gharamti, M. E.

2014-03-01

Isothermal compositional flow models require coupling transient compressible flows and advective transport systems of various chemical species in subsurface porous media. Building such numerical models is quite challenging and may be subject to many sources of uncertainties because of possible incomplete representation of some geological parameters that characterize the system\\'s processes. Advanced data assimilation methods, such as the ensemble Kalman filter (EnKF), can be used to calibrate these models by incorporating available data. In this work, we consider the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components. We carry out state-parameter estimation experiments using joint and dual updating schemes in the context of the EnKF with a two-dimensional single-phase compositional flow model (CFM). Quantitative and statistical analyses are performed to evaluate and compare the performance of the assimilation schemes. Our results indicate that including chemical composition data significantly enhances the accuracy of the permeability estimates. In addition, composition data provide more information to estimate system states and parameters than do standard pressure data. The dual state-parameter estimation scheme provides about 10% more accurate permeability estimates on average than the joint scheme when implemented with the same ensemble members, at the cost of twice more forward model integrations. At similar computational cost, the dual approach becomes only beneficial after using large enough ensembles.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

Science.gov (United States)

Csiszar, Susan A; Meyer, David E; Dionisio, Kathie L; Egeghy, Peter; Isaacs, Kristin K; Price, Paul S; Scanlon, Kelly A; Tan, Yu-Mei; Thomas, Kent; Vallero, Daniel; Bare, Jane C

2016-11-01

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

Science.gov (United States)

Chen, Chia-Hsiu; Tanaka, Kenichi; Funatsu, Kimito

2018-04-22

The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λ abs and λ em , respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.

Using game theory to improve safety within chemical industrial parks

CERN Document Server

Reniers, Genserik

2013-01-01

Though the game-theoretic approach has been vastly studied and utilized in relation to economics of industrial organizations, it has hardly been used to tackle safety management in multi-plant chemical industrial settings. Using Game Theory for Improving Safety within Chemical Industrial Parks presents an in-depth discussion of game-theoretic modelling which may be applied to improve cross-company prevention and -safety management in a chemical industrial park.   By systematically analyzing game-theoretic models and approaches in relation to managing safety in chemical industrial parks, Using Game Theory for Improving Safety within Chemical Industrial Parks explores the ways game theory can predict the outcome of complex strategic investment decision making processes involving several adjacent chemical plants. A number of game-theoretic decision models are discussed to provide strategic tools for decision-making situations.   Offering clear and straightforward explanations of methodologies, Using Game Theor...

Coupling between solute transport and chemical reactions models. Acoplamiento de modelos de transporte de solutos y de modelos de reacciones quimicas

Energy Technology Data Exchange (ETDEWEB)

Samper, J.; Ajora, C. (Instituto de Ciencias de la Tierra, CSIC, Barcerlona (Spain))

1993-01-01

During subsurface transport, reactive solutes are subject to a variety of hydrodynamic and chemical processes. The major hydrodynamic processes include advection and convection, dispersion and diffusion. The key chemical processes are complexation including hydrolysis and acid-base reactions, dissolution-precipitation, reduction-oxidation, adsorption and ion exchange. The combined effects of all these processes on solute transport must satisfy the principle of conservation of mass. The statement of conservation of mass for N mobile species leads to N partial differential equations. Traditional solute transport models often incorporate the effects of hydrodynamic processes rigorously but oversimplify chemical interactions among aqueous species. Sophisticated chemical equilibrium models, on the other hand, incorporate a variety of chemical processes but generally assume no-flow systems. In the past decade, coupled models accounting for complex hydrological and chemical processes, with varying degrees of sophistication, have been developed. The existing models of reactive transport employ two basic sets of equations. The transport of solutes is described by a set of partial differential equations, and the chemical processes, under the assumption of equilibrium, are described by a set of nonlinear algebraic equations. An important consideration in any approach is the choice of primary dependent variables. Most existing models cannot account for the complete set of chemical processes, cannot be easily extended to include mixed chemical equilibria and kinetics, and cannot handle practical two and three dimensional problems. The difficulties arise mainly from improper selection of the primary variables in the transport equations. (Author) 38 refs.

First-Principles Approach to Model Electrochemical Reactions: Understanding the Fundamental Mechanisms behind Mg Corrosion

Science.gov (United States)

Surendralal, Sudarsan; Todorova, Mira; Finnis, Michael W.; Neugebauer, Jörg

2018-06-01

Combining concepts of semiconductor physics and corrosion science, we develop a novel approach that allows us to perform ab initio calculations under controlled potentiostat conditions for electrochemical systems. The proposed approach can be straightforwardly applied in standard density functional theory codes. To demonstrate the performance and the opportunities opened by this approach, we study the chemical reactions that take place during initial corrosion at the water-Mg interface under anodic polarization. Based on this insight, we derive an atomistic model that explains the origin of the anodic hydrogen evolution.

Innovation in Integrated Chemical Product-Process Design - Development through a Model-based Systems Approach

DEFF Research Database (Denmark)

Conte, Elisa

The ‘consumer oriented chemicals based products’ such as shampoos, sunscreens, insect repellents are used everyday by millions of people. They are structured products, constituted of numerous chemicals. This complexity gives the reason for which mainly experimental techniques are still employed...

Modeling the cometary environment using a fluid approach

Science.gov (United States)

Shou, Yinsi

Comets are believed to have preserved the building material of the early solar system and to hold clues to the origin of life on Earth. Abundant remote observations of comets by telescopes and the in-situ measurements by a handful of space missions reveal that the cometary environments are complicated by various physical and chemical processes among the neutral gases and dust grains released from comets, cometary ions, and the solar wind in the interplanetary space. Therefore, physics-based numerical models are in demand to interpret the observational data and to deepen our understanding of the cometary environment. In this thesis, three models using a fluid approach, which include important physical and chemical processes underlying the cometary environment, have been developed to study the plasma, neutral gas, and the dust grains, respectively. Although models based on the fluid approach have limitations in capturing all of the correct physics for certain applications, especially for very low gas density environment, they are computationally much more efficient than alternatives. In the simulations of comet 67P/Churyumov-Gerasimenko at various heliocentric distances with a wide range of production rates, our multi-fluid cometary neutral gas model and multi-fluid cometary dust model have achieved comparable results to the Direct Simulation Monte Carlo (DSMC) model, which is based on a kinetic approach that is valid in all collisional regimes. Therefore, our model is a powerful alternative to the particle-based model, especially for some computationally intensive simulations. Capable of accounting for the varying heating efficiency under various physical conditions in a self-consistent way, the multi-fluid cometary neutral gas model is a good tool to study the dynamics of the cometary coma with different production rates and heliocentric distances. The modeled H2O expansion speeds reproduce the general trend and the speed's nonlinear dependencies of production rate

The TOMCAT global chemical transport model v1.6: description of chemical mechanism and model evaluation

Directory of Open Access Journals (Sweden)

S. A. Monks

2017-08-01

Full Text Available This paper documents the tropospheric chemical mechanism scheme used in the TOMCAT 3-D chemical transport model. The current scheme includes a more detailed representation of hydrocarbon chemistry than previously included in the model, with the inclusion of the emission and oxidation of ethene, propene, butane, toluene and monoterpenes. The model is evaluated against a range of surface, balloon, aircraft and satellite measurements. The model is generally able to capture the main spatial and seasonal features of high and low concentrations of carbon monoxide (CO, ozone (O3, volatile organic compounds (VOCs and reactive nitrogen. However, model biases are found in some species, some of which are common to chemistry models and some that are specific to TOMCAT and warrant further investigation. The most notable of these biases are (1 a negative bias in Northern Hemisphere (NH winter and spring CO and a positive bias in Southern Hemisphere (SH CO throughout the year, (2 a positive bias in NH O3 in summer and a negative bias at high latitudes during SH winter and (3 a negative bias in NH winter C2 and C3 alkanes and alkenes. TOMCAT global mean tropospheric hydroxyl radical (OH concentrations are higher than estimates inferred from observations of methyl chloroform but similar to, or lower than, multi-model mean concentrations reported in recent model intercomparison studies. TOMCAT shows peak OH concentrations in the tropical lower troposphere, unlike other models which show peak concentrations in the tropical upper troposphere. This is likely to affect the lifetime and transport of important trace gases and warrants further investigation.

Consequence and Resilience Modeling for Chemical Supply Chains

Science.gov (United States)

Stamber, Kevin L.; Vugrin, Eric D.; Ehlen, Mark A.; Sun, Amy C.; Warren, Drake E.; Welk, Margaret E.

2011-01-01

The U.S. chemical sector produces more than 70,000 chemicals that are essential material inputs to critical infrastructure systems, such as the energy, public health, and food and agriculture sectors. Disruptions to the chemical sector can potentially cascade to other dependent sectors, resulting in serious national consequences. To address this concern, the U.S. Department of Homeland Security (DHS) tasked Sandia National Laboratories to develop a predictive consequence modeling and simulation capability for global chemical supply chains. This paper describes that capability , which includes a dynamic supply chain simulation platform called N_ABLE(tm). The paper also presents results from a case study that simulates the consequences of a Gulf Coast hurricane on selected segments of the U.S. chemical sector. The case study identified consequences that include impacted chemical facilities, cascading impacts to other parts of the chemical sector. and estimates of the lengths of chemical shortages and recovery . Overall. these simulation results can DHS prepare for and respond to actual disruptions.

Mathematical Modeling of Tin-Free Chemically-Active Antifouling Paint Behavior

DEFF Research Database (Denmark)

Yebra, Diego Meseguer; Kiil, Søren; Dam-Johansen, Kim

2006-01-01

Mathematical modeling has been used to characterize and validate the working mechanisms of tin-free, chemically-active antifouling (AF) paints. The model-based analysis of performance data from lab-scale rotary experiments has shown significant differences between antifouling technologies...... of Chemical Engineers....

An approach to develop chemical intuition for atomistic electron transport calculations using basis set rotations

Energy Technology Data Exchange (ETDEWEB)

Borges, A.; Solomon, G. C. [Department of Chemistry and Nano-Science Center, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen Ø (Denmark)

2016-05-21

Single molecule conductance measurements are often interpreted through computational modeling, but the complexity of these calculations makes it difficult to directly link them to simpler concepts and models. Previous work has attempted to make this connection using maximally localized Wannier functions and symmetry adapted basis sets, but their use can be ambiguous and non-trivial. Starting from a Hamiltonian and overlap matrix written in a hydrogen-like basis set, we demonstrate a simple approach to obtain a new basis set that is chemically more intuitive and allows interpretation in terms of simple concepts and models. By diagonalizing the Hamiltonians corresponding to each atom in the molecule, we obtain a basis set that can be partitioned into pseudo-σ and −π and allows partitioning of the Landuaer-Büttiker transmission as well as create simple Hückel models that reproduce the key features of the full calculation. This method provides a link between complex calculations and simple concepts and models to provide intuition or extract parameters for more complex model systems.

The modelling of direct chemical kinetic effects in turbulent flames

Energy Technology Data Exchange (ETDEWEB)

Lindstet, R.P. [Imperial College of Science, Technology and Medicine, London (United Kingdom). Dept. of Mechanical Engineering

2000-06-01

Combustion chemistry-related effects have traditionally been of secondary importance in the design of gas turbine combustors. However, the need to deal with issues such as flame stability, relight and pollutant emissions has served to bring chemical kinetics and the coupling of finite rate chemistry with turbulent flow fields to the centre of combustor design. Indeed, improved cycle efficiency and more stringent environmental legislation, as defined by the ICAO, are current key motivators in combustor design. Furthermore, lean premixed prevaporized (LPP) combustion systems, increasingly used for power generation, often operate close to the lean blow-off limit and are prone to extinction/reignition type phenomena. Thus, current key design issues require that direct chemical kinetic effects be accounted for accurately in any simulation procedure. The transported probability density function (PDF) approach uniquely offers the potential of facilitating the accurate modelling of such effects. The present paper thus assesses the ability of this technique to model kinetically controlled phenomena, such as carbon monoxide emissions and flame blow-off, through the application of a transported PDF method closed at the joint scalar level. The closure for the velocity field is at the second moment level, and a key feature of the present work is the use of comprehensive chemical kinetic mechanisms. The latter are derived from recent work by Lindstedt and co-workers that has resulted in a compact 141 reactions and 28 species mechanism for LNG combustion. The systematically reduced form used here features 14 independent C/H/O scalars, with the remaining species incorporated via steady state approximations. Computations have been performed for hydrogen/carbon dioxide and methane flames. The former (high Reynolds number) flames permit an assessment of the modelling of flame blow-off, and the methane flame has been selected to obtain an indication of the influence of differential

Atomistic-level non-equilibrium model for chemically reactive systems based on steepest-entropy-ascent quantum thermodynamics

International Nuclear Information System (INIS)

Li, Guanchen; Al-Abbasi, Omar; Von Spakovsky, Michael R

2014-01-01

This paper outlines an atomistic-level framework for modeling the non-equilibrium behavior of chemically reactive systems. The framework called steepest- entropy-ascent quantum thermodynamics (SEA-QT) is based on the paradigm of intrinsic quantum thermodynamic (IQT), which is a theory that unifies quantum mechanics and thermodynamics into a single discipline with wide applications to the study of non-equilibrium phenomena at the atomistic level. SEA-QT is a novel approach for describing the state of chemically reactive systems as well as the kinetic and dynamic features of the reaction process without any assumptions of near-equilibrium states or weak-interactions with a reservoir or bath. Entropy generation is the basis of the dissipation which takes place internal to the system and is, thus, the driving force of the chemical reaction(s). The SEA-QT non-equilibrium model is able to provide detailed information during the reaction process, providing a picture of the changes occurring in key thermodynamic properties (e.g., the instantaneous species concentrations, entropy and entropy generation, reaction coordinate, chemical affinities, reaction rate, etc). As an illustration, the SEA-QT framework is applied to an atomistic-level chemically reactive system governed by the reaction mechanism F + H 2 ↔ FH + H

Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer.

Science.gov (United States)

Castonguay, Thomas C; Wang, Feng

2008-03-28

In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

Formal modeling of a system of chemical reactions under uncertainty.

Science.gov (United States)

Ghosh, Krishnendu; Schlipf, John

2014-10-01

We describe a novel formalism representing a system of chemical reactions, with imprecise rates of reactions and concentrations of chemicals, and describe a model reduction method, pruning, based on the chemical properties. We present two algorithms, midpoint approximation and interval approximation, for construction of efficient model abstractions with uncertainty in data. We evaluate computational feasibility by posing queries in computation tree logic (CTL) on a prototype of extracellular-signal-regulated kinase (ERK) pathway.

Modeling Electric Double-Layers Including Chemical Reaction Effects

DEFF Research Database (Denmark)

Paz-Garcia, Juan Manuel; Johannesson, Björn; Ottosen, Lisbeth M.

2014-01-01

A physicochemical and numerical model for the transient formation of an electric double-layer between an electrolyte and a chemically-active flat surface is presented, based on a finite elements integration of the nonlinear Nernst-Planck-Poisson model including chemical reactions. The model works...... for symmetric and asymmetric multi-species electrolytes and is not limited to a range of surface potentials. Numerical simulations are presented, for the case of a CaCO3 electrolyte solution in contact with a surface with rate-controlled protonation/deprotonation reactions. The surface charge and potential...... are determined by the surface reactions, and therefore they depends on the bulk solution composition and concentration...

Two-Compartment Pharmacokinetic Models for Chemical Engineers

Science.gov (United States)

Kanneganti, Kumud; Simon, Laurent

2011-01-01

The transport of potassium permanganate between two continuous-stirred vessels was investigated to help chemical and biomedical engineering students understand two-compartment pharmacokinetic models. Concepts of modeling, mass balance, parameter estimation and Laplace transform were applied to the two-unit process. A good agreement was achieved…

Bringing Science and Pragmatism together - a Tiered Approach for Modelling Toxicological Impacts in LCA

DEFF Research Database (Denmark)

Guinée, J; De Koning, A; Pennington, David W.

2004-01-01

for as broad a range of chemicals as possible: 1) A base model representing a state-of-the-art multimedia model and 2) a simple model derived from the base model using statistical tools. Discussion. A preliminary decision tree for using the OMNIITOX information system (IS) is presented. The decision tree aims...... categories. The OMNIITOX project is developing a tiered model approach for this. It is foreseen that a first version of the base model will be ready in late summer of 2004, whereas a first version of the simple base model is expected a few months later....

Chemical Kinetic Models for Advanced Engine Combustion

Energy Technology Data Exchange (ETDEWEB)

Pitz, William J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mehl, Marco [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Westbrook, Charles K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-10-22

The objectives for this project are as follows: Develop detailed chemical kinetic models for fuel components used in surrogate fuels for compression ignition (CI), homogeneous charge compression ignition (HCCI) and reactivity-controlled compression-ignition (RCCI) engines; and Combine component models into surrogate fuel models to represent real transportation fuels. Use them to model low-temperature combustion strategies in HCCI, RCCI, and CI engines that lead to low emissions and high efficiency.

A nonlinear isobologram model with Box-Cox transformation to both sides for chemical mixtures.

Science.gov (United States)

Chen, D G; Pounds, J G

1998-12-01

The linear logistical isobologram is a commonly used and powerful graphical and statistical tool for analyzing the combined effects of simple chemical mixtures. In this paper a nonlinear isobologram model is proposed to analyze the joint action of chemical mixtures for quantitative dose-response relationships. This nonlinear isobologram model incorporates two additional new parameters, Ymin and Ymax, to facilitate analysis of response data that are not constrained between 0 and 1, where parameters Ymin and Ymax represent the minimal and the maximal observed toxic response. This nonlinear isobologram model for binary mixtures can be expressed as [formula: see text] In addition, a Box-Cox transformation to both sides is introduced to improve the goodness of fit and to provide a more robust model for achieving homogeneity and normality of the residuals. Finally, a confidence band is proposed for selected isobols, e.g., the median effective dose, to facilitate graphical and statistical analysis of the isobologram. The versatility of this approach is demonstrated using published data describing the toxicity of the binary mixtures of citrinin and ochratoxin as well as a new experimental data from our laboratory for mixtures of mercury and cadmium.

Mining chemical reactions using neighborhood behavior and condensed graphs of reactions approaches.

Science.gov (United States)

de Luca, Aurélie; Horvath, Dragos; Marcou, Gilles; Solov'ev, Vitaly; Varnek, Alexandre

2012-09-24

This work addresses the problem of similarity search and classification of chemical reactions using Neighborhood Behavior (NB) and Condensed Graphs of Reaction (CGR) approaches. The CGR formalism represents chemical reactions as a classical molecular graph with dynamic bonds, enabling descriptor calculations on this graph. Different types of the ISIDA fragment descriptors generated for CGRs in combination with two metrics--Tanimoto and Euclidean--were considered as chemical spaces, to serve for reaction dissimilarity scoring. The NB method has been used to select an optimal combination of descriptors which distinguish different types of chemical reactions in a database containing 8544 reactions of 9 classes. Relevance of NB analysis has been validated in generic (multiclass) similarity search and in clustering with Self-Organizing Maps (SOM). NB-compliant sets of descriptors were shown to display enhanced mapping propensities, allowing the construction of better Self-Organizing Maps and similarity searches (NB and classical similarity search criteria--AUC ROC--correlate at a level of 0.7). The analysis of the SOM clusters proved chemically meaningful CGR substructures representing specific reaction signatures.

An approach in building a chemical compound search engine in oracle database.

Science.gov (United States)

Wang, H; Volarath, P; Harrison, R

2005-01-01

A searching or identifying of chemical compounds is an important process in drug design and in chemistry research. An efficient search engine involves a close coupling of the search algorithm and database implementation. The database must process chemical structures, which demands the approaches to represent, store, and retrieve structures in a database system. In this paper, a general database framework for working as a chemical compound search engine in Oracle database is described. The framework is devoted to eliminate data type constrains for potential search algorithms, which is a crucial step toward building a domain specific query language on top of SQL. A search engine implementation based on the database framework is also demonstrated. The convenience of the implementation emphasizes the efficiency and simplicity of the framework.

Study of the behaviour of trace elements in estuaries: experimental approaches and modeling

International Nuclear Information System (INIS)

Dange, Catherine

2002-01-01

Most of trace elements have a non conservative behavior in estuarine environments. It is the case of cadmium, cobalt and caesium for which the fate in estuarine and coastal zones is largely controlled by their distribution between water and suspended particles, which generally have high residence times or can be definitely deposited in these areas. Metallic contaminants and radionuclides can be present under various species: dissolved (mineral and organic complexes), colloidal and particulate forms (adsorbed, precipitated) or integrated by various mechanisms in the organisms. Such distributions are the result of processes (physical, chemical, biological) which are controlled by many factors (ionic strength, pH, E_h, major cations concentration, nature and concentration of suspended matter, primary production,...). Geochemical modeling is a very useful approach to understand the dynamics of this type of contaminant, especially in the complex systems which are the estuaries. A speciation model was used to simulate the measurements of dissolved and particulate Cd, Co and Cs, taken during various cruises carried out in the Seine, Loire, Gironde and Rhone estuaries. The model is able to reproduce the distribution of metals between the dissolved and particulate phases, and also to evaluate the concentrations of various chemical species (especially those which are most bio-available). The approach presented treats adsorption processes as a formation of inner sphere complexes with functional surface groups (surface complexation model) or as an cationic exchange reaction. The calculation of chemical species takes into account the presence of dissolved ligands or major cations of seawater, which compete with the metal for the surface sites. The model can consider the various natural particle components (metal oxy-hydroxides, organic matter) as individual adsorbent phases or treat natural particles in a 'global manner'. The choice of modeled processes is based on studies of

Students' Visualisation of Chemical Reactions--Insights into the Particle Model and the Atomic Model

Science.gov (United States)

Cheng, Maurice M. W.

2018-01-01

This paper reports on an interview study of 18 Grade 10-12 students' model-based reasoning of a chemical reaction: the reaction of magnesium and oxygen at the submicro level. It has been proposed that chemical reactions can be conceptualised using two models: (i) the "particle model," in which a reaction is regarded as the simple…

Chemical-gene interaction networks and causal reasoning for ...

Science.gov (United States)

Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o

Chemical evolution of galaxies

CERN Document Server

Matteucci, Francesca

2012-01-01

The term “chemical evolution of galaxies” refers to the evolution of abundances of chemical species in galaxies, which is due to nuclear processes occurring in stars and to gas flows into and out of galaxies. This book deals with the chemical evolution of galaxies of all morphological types (ellipticals, spirals and irregulars) and stresses the importance of the star formation histories in determining the properties of stellar populations in different galaxies. The topic is approached in a didactical and logical manner via galaxy evolution models which are compared with observational results obtained in the last two decades: The reader is given an introduction to the concept of chemical abundances and learns about the main stellar populations in our Galaxy as well as about the classification of galaxy types and their main observables. In the core of the book, the construction and solution of chemical evolution models are discussed in detail, followed by descriptions and interpretations of observations of ...

Noninvasive Biomonitoring Approaches to Determine Dosimetry and Risk Following Acute Chemical Exposure: Analysis of Lead or Organophosphate Insecticide in Saliva

International Nuclear Information System (INIS)

Timchalk, Chuck; Poet, Torka S.; Kousba, Ahmed A.; Campbell, James A.; Lin, Yuehe

2004-01-01

There is a need to develop approaches for assessing risk associated with acute exposures to a broad-range of chemical agents and to rapidly determine the potential implications to human health. Non-invasive biomonitoring approaches are being developed using reliable portable analytical systems to quantitate dosimetry utilizing readily obtainable body fluids, such as saliva. Saliva has been used to evaluate a broad range of biomarkers, drugs, and environmental contaminants including heavy metals and pesticides. To advance the application of non-invasive biomonitoring a microfluidic/ electrochemical device has also been developed for the analysis of lead (Pb), using square wave anodic stripping voltammetry. The system demonstrates a linear response over a broad concentration range (1 2000 ppb) and is capable of quantitating saliva Pb in rats orally administered acute doses of Pb-acetate. Appropriate pharmacokinetic analyses have been used to quantitate systemic dosimetry based on determination of saliva Pb concentrations. In addition, saliva has recently been used to quantitate dosimetry following exposure to the organophosphate insecticide chlorpyrifos in a rodent model system by measuring the major metabolite, trichloropyridinol, and saliva cholinesterase inhibition following acute exposures. These results suggest that technology developed for non-invasive biomonitoring can provide a sensitive, and portable analytical tool capable of assessing exposure and risk in real-time. By coupling these non-invasive technologies with pharmacokinetic modeling it is feasible to rapidly quantitate acute exposure to a broad range of chemical agents. In summary, it is envisioned that once fully developed, these monitoring and modeling approaches will be useful for accessing acute exposure and health risk

Some approaches to the quantum-chemical theory of heterogeneous catalysis

Energy Technology Data Exchange (ETDEWEB)

Zhidomirov, G M

1977-09-01

A discussion of mathematical methods, models, and parameters used in various quantum-chemical descriptions of chemisorption and reaction at silica and aluminosilicate surfaces covers the continuous-surface model, the cluster model of the surface, the variation of pseudo-atom parameters to reduce the magnitude of boundary effects in the cluster model, the calculation of individual bond strengths in chemisorbed molecules, dissociative adsorption, applications to adsorption on silica and aluminosilicates, the mechanisms of hydrogen-deuterium exchange, etc. Diagrams, graphs, and 42 references.

Resolving Nuclear Reactor Lifetime Extension Questions: A Combined Multiscale Modeling and Positron Characterization approach

International Nuclear Information System (INIS)

Wirth, B; Asoka-Kumar, P; Denison, A; Glade, S; Howell, R; Marian, J; Odette, G; Sterne, P

2004-01-01

The objective of this work is to determine the chemical composition of nanometer precipitates responsible for irradiation hardening and embrittlement of reactor pressure vessel steels, which threaten to limit the operating lifetime of nuclear power plants worldwide. The scientific approach incorporates computational multiscale modeling of radiation damage and microstructural evolution in Fe-Cu-Ni-Mn alloys, and experimental characterization by positron annihilation spectroscopy and small angle neutron scattering. The modeling and experimental results are

On microscopic simulations of systems with model chemical reactions

International Nuclear Information System (INIS)

Gorecki, J.; Gorecka, J.N.

1998-01-01

Large scale computer simulations of model chemical systems play the role of idealized experiments in which theories may be tested. In this paper we present two applications of microscopic simulations based on the reactive hard sphere model. We investigate the influence of internal fluctuations on an oscillating chemical system and observe how they modify the phase portrait of it. Another application, we consider, is concerned with the propagation of a chemical wave front associated with a thermally activated reaction. It is shown that the nonequilibrium effects increase the front velocity if compared with the velocity of the front generated by a nonactivated process characterized by the same rate constant. (author)

The current status of exposure-driven approaches for chemical safety assessment: A cross-sector perspective.

Science.gov (United States)

Sewell, Fiona; Aggarwal, Manoj; Bachler, Gerald; Broadmeadow, Alan; Gellatly, Nichola; Moore, Emma; Robinson, Sally; Rooseboom, Martijn; Stevens, Alexander; Terry, Claire; Burden, Natalie

2017-08-15

For the purposes of chemical safety assessment, the value of using non-animal (in silico and in vitro) approaches and generating mechanistic information on toxic effects is being increasingly recognised. For sectors where in vivo toxicity tests continue to be a regulatory requirement, there has been a parallel focus on how to refine studies (i.e. reduce suffering and improve animal welfare) and increase the value that in vivo data adds to the safety assessment process, as well as where to reduce animal numbers where possible. A key element necessary to ensure the transition towards successfully utilising both non-animal and refined safety testing is the better understanding of chemical exposure. This includes approaches such as measuring chemical concentrations within cell-based assays and during in vivo studies, understanding how predicted human exposures relate to levels tested, and using existing information on human exposures to aid in toxicity study design. Such approaches promise to increase the human relevance of safety assessment, and shift the focus from hazard-driven to risk-driven strategies similar to those used in the pharmaceutical sectors. Human exposure-based safety assessment offers scientific and 3Rs benefits across all sectors marketing chemical or medicinal products. The UK's National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) convened an expert working group of scientists across the agrochemical, industrial chemical and pharmaceutical industries plus a contract research organisation (CRO) to discuss the current status of the utilisation of exposure-driven approaches, and the challenges and potential next steps for wider uptake and acceptance. This paper summarises these discussions, highlights the challenges - particularly those identified by industry - and proposes initial steps for moving the field forward. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Chemical pattern of brazilian apples: a chemometric approach based on the Fuji and Gala varieties

OpenAIRE

Vieira,Renato Giovanetti; Prestes,Rosilene Aparecida; Denardi,Frederico; Nogueira,Alessandro; Wosiacki,Gilvan

2011-01-01

The chemical composition of apple juices may be used to discriminate between the varieties for consumption and those for raw material. Fuji and Gala have a chemical pattern that can be used for this classification. Multivariate methods correlate independent continuous chemical descriptors with the categorical apple variety. Three main descriptors of apple juice were selected: malic acid, total reducing sugar and total phenolic compounds. A chemometric approach, employing PCA and SIMCA, was us...

Chemical reaction networks as a model to describe UVC- and radiolytically-induced reactions of simple compounds.

Science.gov (United States)

Dondi, Daniele; Merli, Daniele; Albini, Angelo; Zeffiro, Alberto; Serpone, Nick

2012-05-01

When a chemical system is submitted to high energy sources (UV, ionizing radiation, plasma sparks, etc.), as is expected to be the case of prebiotic chemistry studies, a plethora of reactive intermediates could form. If oxygen is present in excess, carbon dioxide and water are the major products. More interesting is the case of reducing conditions where synthetic pathways are also possible. This article examines the theoretical modeling of such systems with random-generated chemical networks. Four types of random-generated chemical networks were considered that originated from a combination of two connection topologies (viz., Poisson and scale-free) with reversible and irreversible chemical reactions. The results were analyzed taking into account the number of the most abundant products required for reaching 50% of the total number of moles of compounds at equilibrium, as this may be related to an actual problem of complex mixture analysis. The model accounts for multi-component reaction systems with no a priori knowledge of reacting species and the intermediates involved if system components are sufficiently interconnected. The approach taken is relevant to an earlier study on reactions that may have occurred in prebiotic systems where only a few compounds were detected. A validation of the model was attained on the basis of results of UVC and radiolytic reactions of prebiotic mixtures of low molecular weight compounds likely present on the primeval Earth.

Generation of Complex Karstic Conduit Networks with a Hydro-chemical Model

Science.gov (United States)

De Rooij, R.; Graham, W. D.

2016-12-01

The discrete-continuum approach is very well suited to simulate flow and solute transport within karst aquifers. Using this approach, discrete one-dimensional conduits are embedded within a three-dimensional continuum representative of the porous limestone matrix. Typically, however, little is known about the geometry of the karstic conduit network. As such the discrete-continuum approach is rarely used for practical applications. It may be argued, however, that the uncertainty associated with the geometry of the network could be handled by modeling an ensemble of possible karst conduit networks within a stochastic framework. We propose to generate stochastically realistic karst conduit networks by simulating the widening of conduits as caused by the dissolution of limestone over geological relevant timescales. We illustrate that advanced numerical techniques permit to solve the non-linear and coupled hydro-chemical processes efficiently, such that relatively large and complex networks can be generated in acceptable time frames. Instead of specifying flow boundary conditions on conduit cells to recharge the network as is typically done in classical speleogenesis models, we specify an effective rainfall rate over the land surface and let model physics determine the amount of water entering the network. This is advantageous since the amount of water entering the network is extremely difficult to reconstruct, whereas the effective rainfall rate may be quantified using paleoclimatic data. Furthermore, we show that poorly known flow conditions may be constrained by requiring a realistic flow field. Using our speleogenesis model we have investigated factors that influence the geometry of simulated conduit networks. We illustrate that our model generates typical branchwork, network and anastomotic conduit systems. Flow, solute transport and water ages in karst aquifers are simulated using a few illustrative networks.

Development of hydrogeological modelling approaches for assessment of consequences of hazardous accidents at nuclear power plants

International Nuclear Information System (INIS)

Rumynin, V.G.; Mironenko, V.A.; Konosavsky, P.K.; Pereverzeva, S.A.

1994-07-01

This paper introduces some modeling approaches for predicting the influence of hazardous accidents at nuclear reactors on groundwater quality. Possible pathways for radioactive releases from nuclear power plants were considered to conceptualize boundary conditions for solving the subsurface radionuclides transport problems. Some approaches to incorporate physical-and-chemical interactions into transport simulators have been developed. The hydrogeological forecasts were based on numerical and semi-analytical scale-dependent models. They have been applied to assess the possible impact of the nuclear power plants designed in Russia on groundwater reservoirs

Using chemical benchmarking to determine the persistence of chemicals in a Swedish lake.

Science.gov (United States)

Zou, Hongyan; Radke, Michael; Kierkegaard, Amelie; MacLeod, Matthew; McLachlan, Michael S

2015-02-03

It is challenging to measure the persistence of chemicals under field conditions. In this work, two approaches for measuring persistence in the field were compared: the chemical mass balance approach, and a novel chemical benchmarking approach. Ten pharmaceuticals, an X-ray contrast agent, and an artificial sweetener were studied in a Swedish lake. Acesulfame K was selected as a benchmark to quantify persistence using the chemical benchmarking approach. The 95% confidence intervals of the half-life for transformation in the lake system ranged from 780-5700 days for carbamazepine to benchmarking approach agreed well with those from the mass balance approach (1-21% difference), indicating that chemical benchmarking can be a valid and useful method to measure the persistence of chemicals under field conditions. Compared to the mass balance approach, the benchmarking approach partially or completely eliminates the need to quantify mass flow of chemicals, so it is particularly advantageous when the quantification of mass flow of chemicals is difficult. Furthermore, the benchmarking approach allows for ready comparison and ranking of the persistence of different chemicals.

Practical modeling approaches for geological storage of carbon dioxide.

Science.gov (United States)

Celia, Michael A; Nordbotten, Jan M

2009-01-01

The relentless increase of anthropogenic carbon dioxide emissions and the associated concerns about climate change have motivated new ideas about carbon-constrained energy production. One technological approach to control carbon dioxide emissions is carbon capture and storage, or CCS. The underlying idea of CCS is to capture the carbon before it emitted to the atmosphere and store it somewhere other than the atmosphere. Currently, the most attractive option for large-scale storage is in deep geological formations, including deep saline aquifers. Many physical and chemical processes can affect the fate of the injected CO2, with the overall mathematical description of the complete system becoming very complex. Our approach to the problem has been to reduce complexity as much as possible, so that we can focus on the few truly important questions about the injected CO2, most of which involve leakage out of the injection formation. Toward this end, we have established a set of simplifying assumptions that allow us to derive simplified models, which can be solved numerically or, for the most simplified cases, analytically. These simplified models allow calculation of solutions to large-scale injection and leakage problems in ways that traditional multicomponent multiphase simulators cannot. Such simplified models provide important tools for system analysis, screening calculations, and overall risk-assessment calculations. We believe this is a practical and important approach to model geological storage of carbon dioxide. It also serves as an example of how complex systems can be simplified while retaining the essential physics of the problem.

Introduction to the Monte Carlo project and the approach to the validation of probabilistic models of dietary exposure to selected food chemicals

NARCIS (Netherlands)

Gibney, M.J.; Voet, van der H.

2003-01-01

The Monte Carlo project was established to allow an international collaborative effort to define conceptual models for food chemical and nutrient exposure, to define and validate the software code to govern these models, to provide new or reconstructed databases for validation studies, and to use

Thermal-chemical Mantle Convection Models With Adaptive Mesh Refinement

Science.gov (United States)

Leng, W.; Zhong, S.

2008-12-01

In numerical modeling of mantle convection, resolution is often crucial for resolving small-scale features. New techniques, adaptive mesh refinement (AMR), allow local mesh refinement wherever high resolution is needed, while leaving other regions with relatively low resolution. Both computational efficiency for large- scale simulation and accuracy for small-scale features can thus be achieved with AMR. Based on the octree data structure [Tu et al. 2005], we implement the AMR techniques into the 2-D mantle convection models. For pure thermal convection models, benchmark tests show that our code can achieve high accuracy with relatively small number of elements both for isoviscous cases (i.e. 7492 AMR elements v.s. 65536 uniform elements) and for temperature-dependent viscosity cases (i.e. 14620 AMR elements v.s. 65536 uniform elements). We further implement tracer-method into the models for simulating thermal-chemical convection. By appropriately adding and removing tracers according to the refinement of the meshes, our code successfully reproduces the benchmark results in van Keken et al. [1997] with much fewer elements and tracers compared with uniform-mesh models (i.e. 7552 AMR elements v.s. 16384 uniform elements, and ~83000 tracers v.s. ~410000 tracers). The boundaries of the chemical piles in our AMR code can be easily refined to the scales of a few kilometers for the Earth's mantle and the tracers are concentrated near the chemical boundaries to precisely trace the evolvement of the boundaries. It is thus very suitable for our AMR code to study the thermal-chemical convection problems which need high resolution to resolve the evolvement of chemical boundaries, such as the entrainment problems [Sleep, 1988].

Computational approaches to the chemical conversion of carbon dioxide

Energy Technology Data Exchange (ETDEWEB)

Cheng, Daojian; Negreiros, Fabio R.; Apra, Edoardo; Fortunelli, Alessandro

2013-06-01

The conversion of CO2 into fuels and chemicals is viewed as an attractive route for controlling the atmospheric concentration of this greenhouse gas and recycling it, but its industrial application is limited by the low selectivity and activity of the current catalysts. Theoretical modeling, in particular density-functional theory (DFT) simulations, provides a powerful and effective tool to discover chemical reaction mechanisms and design new catalysts for the chemical conversion of CO2, overcoming the repetitious and time/labor consuming trial-and-error experimental processes. In this article we give a comprehensive survey of recent advances on mechanism determination by DFT calculations for the catalytic hydrogenation of CO2 into CO, CH4, CH3OH, and HCOOH, and CO2 methanation, as well as the photo- and electrochemical reduction of CO2. DFT-guided design procedures of new catalytic systems are also reviewed, and challenges and perspectives in this field are outlined.

Enhancing sewage sludge dewaterability by bioleaching approach with comparison to other physical and chemical conditioning methods.

Science.gov (United States)

Liu, Fenwu; Zhou, Jun; Wang, Dianzhan; Zhou, Lixiang

2012-01-01

The sewage sludge conditioning process is critical to improve the sludge dewaterability prior to mechanical dewatering. Traditionally, sludge is conditioned by physical or chemical approaches, mostly with the addition of inorganic or organic chemicals. Here we report that bioleaching, an efficient and economical microbial method for the removal of sludge-borne heavy metals, also plays a significant role in enhancing sludge dewaterability. The effects of bioleaching and physical or chemical approaches on sludge dewaterability were compared. The conditioning result of bioleaching by Acidithiobacillus thiooxidans and Acidithiobacillus ferrooxidans on sludge dewatering was investigated and compared with the effects of hydrothermal (121 degrees C for 2 hr), microwave (1050 W for 50 sec), ultrasonic (250 W for 2 min), and chemical conditioning (24% ferric chloride and 68% calcium oxide; dry basis). The results show that the specific resistance to filtration (SRF) or capillary suction time (CST) of sludge is decreased by 93.1% or 74.1%, respectively, after fresh sludge is conditioned by bioleaching, which is similar to chemical conditioning treatment with ferric chloride and calcium oxide but much more effective than other conditioning approaches including hydrothermal, microwave, and ultrasonic conditioning. Furthermore, after sludge dewatering, bioleached sludge filtrate contains the lowest concentrations of chroma (18 times), COD (542 mg/L), total N (TN, 300 mg/L), NH4(+)-N (208 mg/L), and total P (TP, 2 mg/L) while the hydrothermal process resulted in the highest concentration of chroma (660 times), COD (18,155 mg/L), TN (472 mg/L), NH4(+)-N (381 mg/L), and TP (191 mg/L) among these selected conditioning methods. Moreover, unlike chemical conditioning, sludge bioleaching does not result in a significant reduction of organic matter, TN, and TP in the resulting dewatered sludge cake. Therefore, considering sludge dewaterability and the chemical properties of sludge

Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization.

Science.gov (United States)

Wood, Matthew D; Plourde, Kenton; Larkin, Sabrina; Egeghy, Peter P; Williams, Antony J; Zemba, Valerie; Linkov, Igor; Vallero, Daniel A

2018-05-11

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics. © 2018 Society for Risk Analysis.

A chemical model for the interstellar medium in galaxies

OpenAIRE

Bovino, S.; Grassi, Tommaso; Capelo, P. R.; Schleicher, D. R. G.; Banerjee, R.

2016-01-01

Aims: We present and test chemical models for three-dimensional hydrodynamical simulations of galaxies. We explore the effect of changing key parameters such as metallicity, radiation, and non-equilibrium versus equilibrium metal cooling approximations on the transition between the gas phases in the interstellar medium. Methods: The microphysics was modelled by employing the public chemistry package KROME, and the chemical networks were tested to work in a wide range of densities and temp...

A global framework to model spatial ecosystems exposure to home and personal care chemicals in Asia.

Science.gov (United States)

Wannaz, Cedric; Franco, Antonio; Kilgallon, John; Hodges, Juliet; Jolliet, Olivier

2018-05-01

This paper analyzes spatially ecosystem exposure to home and personal care (HPC) chemicals, accounting for market data and environmental processes in hydrological water networks, including multi-media fate and transport. We present a global modeling framework built on ScenAT (spatial scenarios of emission), SimpleTreat (sludge treatment plants), and Pangea (spatial multi-scale multimedia fate and transport of chemicals), that we apply across Asia to four chemicals selected to cover a variety of applications, volumes of production and emission, and physico-chemical and environmental fate properties: the anionic surfactant linear alkylbenzene sulphonate (LAS), the antimicrobial triclosan (TCS), the personal care preservative methyl paraben (MeP), and the emollient decamethylcyclopentasiloxane (D5). We present maps of predicted environmental concentrations (PECs) and compare them with monitored values. LAS emission levels and PECs are two to three orders of magnitude greater than for other substances, yet the literature about monitored levels of LAS in Asia is very limited. We observe a good agreement for TCS in freshwater (Pearson r=0.82, for 253 monitored values covering 12 streams), a moderate agreement in general, and a significant model underestimation for MeP in sediments. While most differences could be explained by uncertainty in both chemical/hydrological parameters (DT50 water , DT50 sediments , K oc , f oc , TSS) and monitoring sites (e.g. spatial/temporal design), the underestimation of MeP concentrations in sediments may involve potential natural sources. We illustrate the relevance of local evaluations for short-lived substances in fresh water (LAS, MeP), and their inadequacy for substances with longer half-lives (TCS, D5). This framework constitutes a milestone towards higher tier exposure modeling approaches for identifying areas of higher chemical concentration, and linking large-scale fate modeling with (sub) catchment-scale ecological scenarios; a

New Chemical Kinetics Approach for DSMC Applications to Nonequilibrium Flows, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — A new chemical kinetics model and database will be developed for aerothermodynamic analyses on entry vehicles. Unique features of this model include (1) the ability...

New Chemical Kinetics Approach for DSMC Applications to Nonequilibrium Flows, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — A new chemical kinetics model and database will be developed for aerothermodynamic analyses on entry vehicles. Unique features of this model include (1) the ability...

Modeling chemical reactions for drug design.

Science.gov (United States)

Gasteiger, Johann

2007-01-01

Chemical reactions are involved at many stages of the drug design process. This starts with the analysis of biochemical pathways that are controlled by enzymes that might be downregulated in certain diseases. In the lead discovery and lead optimization process compounds have to be synthesized in order to test them for their biological activity. And finally, the metabolism of a drug has to be established. A better understanding of chemical reactions could strongly help in making the drug design process more efficient. We have developed methods for quantifying the concepts an organic chemist is using in rationalizing reaction mechanisms. These methods allow a comprehensive modeling of chemical reactivity and thus are applicable to a wide variety of chemical reactions, from gas phase reactions to biochemical pathways. They are empirical in nature and therefore allow the rapid processing of large sets of structures and reactions. We will show here how methods have been developed for the prediction of acidity values and of the regioselectivity in organic reactions, for designing the synthesis of organic molecules and of combinatorial libraries, and for furthering our understanding of enzyme-catalyzed reactions and of the metabolism of drugs.

A coupled model between mechanical deformation and chemical diffusion: An explanation for the preservation of chemical zonation in plagioclase at high temperatures

Science.gov (United States)

Zhong, Xin; Vrijmoed, Johannes; Moulas, Evangelos; Tajcmanová, Lucie

2016-04-01

Compositional zoning in metamorphic minerals have been generally recognized as an important geological feature to decipher the metamorphic history of rocks. The observed chemical zoning of, e.g. garnet, is commonly interpreted as disequilibrium between the fractionated inner core and the surrounding matrix. However, chemically zoned minerals were also observed in high grade rocks (T>800 degree C) where the duration of metamorphic processes was independently dated to take several Ma. This implies that temperature may not be the only factor that controls diffusion timescales, and grain scale pressure variation was proposed to be a complementary factor that may significantly contribute to the formation and preservation of chemical zoning in high temperature metamorphic minerals [Tajcmanová 2013, 2015]. Here, a coupled model is developed to simulate viscous deformation and chemical diffusion. The numerical approach considers the conservation of mass, momentum, and a constitutive relation developed from equilibrium thermodynamics. A compressible viscoelastic rheology is applied, which associates the volumetric change triggered by deformation and diffusion to a change of pressure. The numerical model is applied to the chemically zoned plagioclase rim described by [Tajcmanová 2014]. The diffusion process operating during the plagioclase rim formation can lead to a development of a pressure gradient. Such a pressure gradient, if maintained during ongoing viscous relaxation, can lead to the preservation of the observed chemical zonation in minerals. An important dimensionless number, the Deborah number, is defined as the ratio between the Maxwell viscoelastic relaxation time and the characteristic diffusion time. It characterizes the relative influence between the maintenance of grain scale pressure variation and chemical diffusion. Two extreme regimes are shown: the mechanically-controlled regime (high Deborah number) and diffusion-controlled regime (low Deborah number

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

Science.gov (United States)

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

Sorption kinetics and microbial biodegradation activity of hydrophobic chemicals in sewage sludge: Model and measurements based on free concentrations

NARCIS (Netherlands)

Artola-Garicano, E.; Borkent, I.; Damen, K.; Jager, T.; Vaes, W.H.J.

2003-01-01

In the current study, a new method is introduced with which the rate-limiting factor of biodegradation processes of hydrophobic chemicals in organic and aqueous systems can be determined. The novelty of this approach lies in the combination of a free concentration-based kinetic model with

Center for Integrated Nanotechnologies (CINT) Chemical Release Modeling Evaluation

Energy Technology Data Exchange (ETDEWEB)

Stirrup, Timothy Scott [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-12-20

This evaluation documents the methodology and results of chemical release modeling for operations at Building 518, Center for Integrated Nanotechnologies (CINT) Core Facility. This evaluation is intended to supplement an update to the CINT [Standalone] Hazards Analysis (SHA). This evaluation also updates the original [Design] Hazards Analysis (DHA) completed in 2003 during the design and construction of the facility; since the original DHA, additional toxic materials have been evaluated and modeled to confirm the continued low hazard classification of the CINT facility and operations. This evaluation addresses the potential catastrophic release of the current inventory of toxic chemicals at Building 518 based on a standard query in the Chemical Information System (CIS).

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

Energy Technology Data Exchange (ETDEWEB)

Andrews, Brett H. [PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260 (United States); Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A., E-mail: andrewsb@pitt.edu [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States)

2017-02-01

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

International Nuclear Information System (INIS)

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A.

2017-01-01

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

Modeling of chemical exergy of agricultural biomass using improved general regression neural network

International Nuclear Information System (INIS)

Huang, Y.W.; Chen, M.Q.; Li, Y.; Guo, J.

2016-01-01

A comprehensive evaluation for energy potential contained in agricultural biomass was a vital step for energy utilization of agricultural biomass. The chemical exergy of typical agricultural biomass was evaluated based on the second law of thermodynamics. The chemical exergy was significantly influenced by C and O elements rather than H element. The standard entropy of the samples also was examined based on their element compositions. Two predicted models of the chemical exergy were developed, which referred to a general regression neural network model based upon the element composition, and a linear model based upon the high heat value. An auto-refinement algorithm was firstly developed to improve the performance of regression neural network model. The developed general regression neural network model with K-fold cross-validation had a better ability for predicting the chemical exergy than the linear model, which had lower predicted errors (±1.5%). - Highlights: • Chemical exergies of agricultural biomass were evaluated based upon fifty samples. • Values for the standard entropy of agricultural biomass samples were calculated. • A linear relationship between chemical exergy and HHV of samples was detected. • An improved GRNN prediction model for the chemical exergy of biomass was developed.

Chemical modeling of irreversible reactions in nuclear waste-water-rock systems

International Nuclear Information System (INIS)

Wolery, T.J.

1981-02-01

Chemical models of aqueous geochemical systems are usually built on the concept of thermodynamic equilibrium. Though many elementary reactions in a geochemical system may be close to equilibrium, others may not be. Chemical models of aqueous fluids should take into account that many aqueous redox reactions are among the latter. The behavior of redox reactions may critically affect migration of certain radionuclides, especially the actinides. In addition, the progress of reaction in geochemical systems requires thermodynamic driving forces associated with elementary reactions not at equilibrium, which are termed irreversible reactions. Both static chemical models of fluids and dynamic models of reacting systems have been applied to a wide spectrum of problems in water-rock interactions. Potential applications in nuclear waste disposal range from problems in geochemical aspects of site evaluation to those of waste-water-rock interactions. However, much further work in the laboratory and the field will be required to develop and verify such applications of chemical modeling

A systematic model identification method for chemical transformation pathways – the case of heroin biomarkers in wastewater

DEFF Research Database (Denmark)

Ramin, Pedram; Valverde Pérez, Borja; Polesel, Fabio

2017-01-01

This study presents a novel statistical approach for identifying sequenced chemical transformation pathways in combination with reaction kinetics models. The proposed method relies on sound uncertainty propagation by considering parameter ranges and associated probability distribution obtained...... at any given transformation pathway levels as priors for parameter estimation at any subsequent transformation levels. The method was applied to calibrate a model predicting the transformation in untreated wastewater of six biomarkers, excreted following human metabolism of heroin and codeine. The method....... Results obtained suggest that the method developed has the potential to outperform conventional approaches in terms of prediction accuracy, transformation pathway identification and parameter identifiability. This method can be used in conjunction with optimal experimental designs to effectively identify...

Towards consensus in comparative chemical characterization modeling for LCIA

DEFF Research Database (Denmark)

Hauschild, Michael Zwicky; Bachmann, Till; Huijbregts, Mark

2006-01-01

work within, for instance, the OECD, and guidance from a series of expert workshops held between 2002 and 2005, preliminary guidelines focusing on chemical fate, and human and ecotoxic effects were established. For further elaboration of the fate-, exposure- and effect-sides of the modeling, six models...... by the Task Force and the model providers. While the compared models and their differences are important tools to further advance LCA science, the consensus model is intended to provide a generally agreed and scientifically sound method to calculate consistent characterization factors for use in LCA practice...... and to be the basis of the “recommended practice” for calculation of characterization factors for chemicals under authority of the UNEP/SETAC Life Cycle Initiative....

Simulating Chemical Kinetics Without Differential Equations: A Quantitative Theory Based on Chemical Pathways.

Science.gov (United States)

Bai, Shirong; Skodje, Rex T

2017-08-17

A new approach is presented for simulating the time-evolution of chemically reactive systems. This method provides an alternative to conventional modeling of mass-action kinetics that involves solving differential equations for the species concentrations. The method presented here avoids the need to solve the rate equations by switching to a representation based on chemical pathways. In the Sum Over Histories Representation (or SOHR) method, any time-dependent kinetic observable, such as concentration, is written as a linear combination of probabilities for chemical pathways leading to a desired outcome. In this work, an iterative method is introduced that allows the time-dependent pathway probabilities to be generated from a knowledge of the elementary rate coefficients, thus avoiding the pitfalls involved in solving the differential equations of kinetics. The method is successfully applied to the model Lotka-Volterra system and to a realistic H 2 combustion model.

Physics-based approach to chemical source localization using mobile robotic swarms

Science.gov (United States)

Zarzhitsky, Dimitri

2008-07-01

Recently, distributed computation has assumed a dominant role in the fields of artificial intelligence and robotics. To improve system performance, engineers are combining multiple cooperating robots into cohesive collectives called swarms. This thesis illustrates the application of basic principles of physicomimetics, or physics-based design, to swarm robotic systems. Such principles include decentralized control, short-range sensing and low power consumption. We show how the application of these principles to robotic swarms results in highly scalable, robust, and adaptive multi-robot systems. The emergence of these valuable properties can be predicted with the help of well-developed theoretical methods. In this research effort, we have designed and constructed a distributed physicomimetics system for locating sources of airborne chemical plumes. This task, called chemical plume tracing (CPT), is receiving a great deal of attention due to persistent homeland security threats. For this thesis, we have created a novel CPT algorithm called fluxotaxis that is based on theoretical principles of fluid dynamics. Analytically, we show that fluxotaxis combines the essence, as well as the strengths, of the two most popular biologically-inspired CPT methods-- chemotaxis and anemotaxis. The chemotaxis strategy consists of navigating in the direction of the chemical density gradient within the plume, while the anemotaxis approach is based on an upwind traversal of the chemical cloud. Rigorous and extensive experimental evaluations have been performed in simulated chemical plume environments. Using a suite of performance metrics that capture the salient aspects of swarm-specific behavior, we have been able to evaluate and compare the three CPT algorithms. We demonstrate the improved performance of our fluxotaxis approach over both chemotaxis and anemotaxis in these realistic simulation environments, which include obstacles. To test our understanding of CPT on actual hardware

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

KAUST Repository

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K.

2012-01-01

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system's size. © 2006 IEEE.

Fat versus Thin Threading Approach on GPUs: Application to Stochastic Simulation of Chemical Reactions

KAUST Repository

Klingbeil, Guido

2012-02-01

We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system\\'s size. © 2006 IEEE.

Observed and modelled “chemical weather” during ESCOMPTE

Science.gov (United States)

Dufour, A.; Amodei, M.; Ancellet, G.; Peuch, V.-H.

2005-03-01

The new MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE) three-dimensional multiscale chemistry and transport model (CTM) has been applied to study heavy pollution episodes observed during the ESCOMPTE experiment. The model considers the troposphere and lower stratosphere, and allows the possibility of zooming from the planetary scale down to the regional scale over limited area subdomains. Like this, it generates its own time-dependent chemical boundary conditions in the vertical and in the horizontal. This paper focuses on the evaluation and quantification of uncertainties related to chemical and transport modelling during two intensive observing periods, IOP2 and IOP4 (June 20-26 and July 10-14, 2001, respectively). Simulations are compared to the database of four-dimensional observations, which includes ground-based sites and aircraft measurements, radiosoundings, and quasi-continuous measurements of ozone by LIDARs. Thereby, the observed and modelled day-to-day variabilities in air composition both at the surface and in the vertical have been assessed. Then, three sensitivity studies are conducted concerning boundary conditions, accuracy of the emission dataset, and representation of chemistry. Firstly, to go further in the analysis of chemical boundary conditions, results from the standard grid nesting set-up and altered configurations, relying on climatologies, are compared. Along with other recent studies, this work advocates the systematic coupling of limited-area models with global CTMs, even for regional air quality studies or forecasts. Next, we evaluate the benefits of using the detailed high-resolution emissions inventory of ESCOMPTE: improvements are noticeable both on ozone reactivity and on the concentrations of various species of the ozone photochemical cycle especially primary ones. Finally, we provide some insights on the comparison of two simulations differing only by the parameterisation of chemistry and using two state

Tailor-made Design of Chemical Blends using Decomposition-based Computer-aided Approach

DEFF Research Database (Denmark)

Yunus, Nor Alafiza; Manan, Zainuddin Abd.; Gernaey, Krist

(properties). In this way, first the systematic computer-aided technique establishes the search space, and then narrows it down in subsequent steps until a small number of feasible and promising candidates remain and then experimental work may be conducted to verify if any or all the candidates satisfy......Computer aided technique is an efficient approach to solve chemical product design problems such as design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product attributes...... is decomposed into two stages. The first stage investigates the mixture stability where all unstable mixtures are eliminated and the stable blend candidates are retained for further testing. In the second stage, the blend candidates have to satisfy a set of target properties that are ranked according...

Coarse grain model for coupled thermo-mechano-chemical processes and its application to pressure-induced endothermic chemical reactions

International Nuclear Information System (INIS)

Antillon, Edwin; Banlusan, Kiettipong; Strachan, Alejandro

2014-01-01

We extend a thermally accurate model for coarse grain dynamics (Strachan and Holian 2005 Phys. Rev. Lett. 94 014301) to enable the description of stress-induced chemical reactions in the degrees of freedom internal to the mesoparticles. Similar to the breathing sphere model, we introduce an additional variable that describes the internal state of the particles and whose dynamics is governed both by an internal potential energy function and by interparticle forces. The equations of motion of these new variables are derived from a Hamiltonian and the model exhibits two desired features: total energy conservation and Galilean invariance. We use a simple model material with pairwise interactions between particles and study pressure-induced chemical reactions induced by hydrostatic and uniaxial compression. These examples demonstrate the ability of the model to capture non-trivial processes including the interplay between mechanical, thermal and chemical processes of interest in many applications. (paper)

Rate and State Friction Relation for Nanoscale Contacts: Thermally Activated Prandtl-Tomlinson Model with Chemical Aging

Science.gov (United States)

Tian, Kaiwen; Goldsby, David L.; Carpick, Robert W.

2018-05-01

Rate and state friction (RSF) laws are widely used empirical relationships that describe macroscale to microscale frictional behavior. They entail a linear combination of the direct effect (the increase of friction with sliding velocity due to the reduced influence of thermal excitations) and the evolution effect (the change in friction with changes in contact "state," such as the real contact area or the degree of interfacial chemical bonds). Recent atomic force microscope (AFM) experiments and simulations found that nanoscale single-asperity amorphous silica-silica contacts exhibit logarithmic aging (increasing friction with time) over several decades of contact time, due to the formation of interfacial chemical bonds. Here we establish a physically based RSF relation for such contacts by combining the thermally activated Prandtl-Tomlinson (PTT) model with an evolution effect based on the physics of chemical aging. This thermally activated Prandtl-Tomlinson model with chemical aging (PTTCA), like the PTT model, uses the loading point velocity for describing the direct effect, not the tip velocity (as in conventional RSF laws). Also, in the PTTCA model, the combination of the evolution and direct effects may be nonlinear. We present AFM data consistent with the PTTCA model whereby in aging tests, for a given hold time, static friction increases with the logarithm of the loading point velocity. Kinetic friction also increases with the logarithm of the loading point velocity at sufficiently high velocities, but at a different increasing rate. The discrepancy between the rates of increase of static and kinetic friction with velocity arises from the fact that appreciable aging during static contact changes the energy landscape. Our approach extends the PTT model, originally used for crystalline substrates, to amorphous materials. It also establishes how conventional RSF laws can be modified for nanoscale single-asperity contacts to provide a physically based friction

A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater

Science.gov (United States)

Han, L. F; Plummer, Niel

2016-01-01

13C values.In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14C ages when a curved relationship between the 14C and 13C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14C and δ13C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14C content is derived from the 14C and δ13C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures.The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH4). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited.Failure to recognize the limitations and

Numerical approaches to model perturbation fire in turing pattern formations

Science.gov (United States)

Campagna, R.; Brancaccio, M.; Cuomo, S.; Mazzoleni, S.; Russo, L.; Siettos, K.; Giannino, F.

2017-11-01

Turing patterns were observed in chemical, physical and biological systems described by coupled reaction-diffusion equations. Several models have been formulated proposing the water as the causal mechanism of vegetation pattern formation, but this isn't an exhaustive hypothesis in some natural environments. An alternative explanation has been related to the plant-soil negative feedback. In Marasco et al. [1] the authors explored the hypothesis that both mechanisms contribute in the formation of regular and irregular vegetation patterns. The mathematical model consists in three partial differential equations (PDEs) that take into account for a dynamic balance between biomass, water and toxic compounds. A numerical approach is mandatory also to investigate on the predictions of this kind of models. In this paper we start from the mathematical model described in [1], set the model parameters such that the biomass reaches a stable spatial pattern (spots) and present preliminary studies about the occurrence of perturbing events, such as wildfire, that can affect the regularity of the biomass configuration.

Chapter 7. Management strategies for dwarf mistletoes: Biological, chemical, and genetic approaches

Science.gov (United States)

S. F. Shamoun; L. E. DeWald

2002-01-01

The opportunity and need for management of mistletoe populations with biological, chemical, and genetic approaches are greatest for application to the dwarf mistletoes. Although much information is available on these management strategies (see reviews by Hawksworth 1972, Knutson 1978), significant research and development are still required for these to become...

Identification of Chemical Reactor Plant’s Mathematical Model

OpenAIRE

Pyakullya, Boris Ivanovich; Kladiev, Sergey Nikolaevich

2015-01-01

This work presents a solution of the identification problem of chemical reactor plant’s mathematical model. The main goal is to obtain a mathematical description of a chemical reactor plant from experimental data, which based on plant’s time response measurements. This data consists sequence of measurements for water jacket temperature and information about control input signal, which is used to govern plant’s behavior.

Model tool to describe chemical structures in XML format utilizing structural fragments and chemical ontology.

Science.gov (United States)

Sankar, Punnaivanam; Alain, Krief; Aghila, Gnanasekaran

2010-05-24

We have developed a model structure-editing tool, ChemEd, programmed in JAVA, which allows drawing chemical structures on a graphical user interface (GUI) by selecting appropriate structural fragments defined in a fragment library. The terms representing the structural fragments are organized in fragment ontology to provide a conceptual support. ChemEd describes the chemical structure in an XML document (ChemFul) with rich semantics explicitly encoding the details of the chemical bonding, the hybridization status, and the electron environment around each atom. The document can be further processed through suitable algorithms and with the support of external chemical ontologies to generate understandable reports about the functional groups present in the structure and their specific environment.

Use of Threshold of Toxicological Concern (TTC) with High Throughput Exposure Predictions as a Risk-Based Screening Approach to Prioritize More Than Seven Thousand Chemicals (ASCCT)

Science.gov (United States)

Here, we present results of an approach for risk-based prioritization using the Threshold of Toxicological Concern (TTC) combined with high-throughput exposure (HTE) modelling. We started with 7968 chemicals with calculated population median oral daily intakes characterized by an...

A modeling approach to compare ΣPCB concentrations between congener-specific analyses

Science.gov (United States)

Gibson, Polly P.; Mills, Marc A.; Kraus, Johanna M.; Walters, David M.

2017-01-01

Changes in analytical methods over time pose problems for assessing long-term trends in environmental contamination by polychlorinated biphenyls (PCBs). Congener-specific analyses vary widely in the number and identity of the 209 distinct PCB chemical configurations (congeners) that are quantified, leading to inconsistencies among summed PCB concentrations (ΣPCB) reported by different studies. Here we present a modeling approach using linear regression to compare ΣPCB concentrations derived from different congener-specific analyses measuring different co-eluting groups. The approach can be used to develop a specific conversion model between any two sets of congener-specific analytical data from similar samples (similar matrix and geographic origin). We demonstrate the method by developing a conversion model for an example data set that includes data from two different analytical methods, a low resolution method quantifying 119 congeners and a high resolution method quantifying all 209 congeners. We used the model to show that the 119-congener set captured most (93%) of the total PCB concentration (i.e., Σ209PCB) in sediment and biological samples. ΣPCB concentrations estimated using the model closely matched measured values (mean relative percent difference = 9.6). General applications of the modeling approach include (a) generating comparable ΣPCB concentrations for samples that were analyzed for different congener sets; and (b) estimating the proportional contribution of different congener sets to ΣPCB. This approach may be especially valuable for enabling comparison of long-term remediation monitoring results even as analytical methods change over time. 

A classical Master equation approach to modeling an artificial protein motor

International Nuclear Information System (INIS)

Kuwada, Nathan J.; Blab, Gerhard A.; Linke, Heiner

2010-01-01

Inspired by biomolecular motors, as well as by theoretical concepts for chemically driven nanomotors, there is significant interest in constructing artificial molecular motors. One driving force is the opportunity to create well-controlled model systems that are simple enough to be modeled in detail. A remaining challenge is the fact that such models need to take into account processes on many different time scales. Here we describe use of a classical Master equation approach, integrated with input from Langevin and molecular dynamics modeling, to stochastically model an existing artificial molecular motor concept, the Tumbleweed, across many time scales. This enables us to study how interdependencies between motor processes, such as center-of-mass diffusion and track binding/unbinding, affect motor performance. Results from our model help guide the experimental realization of the proposed motor, and potentially lead to insights that apply to a wider class of molecular motors.

A kinetic-theory approach for computing chemical-reaction rates in upper-atmosphere hypersonic flows.

Science.gov (United States)

Gallis, Michael A; Bond, Ryan B; Torczynski, John R

2009-09-28

Recently proposed molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties (i.e., no macroscopic reaction-rate information) are investigated for chemical reactions occurring in upper-atmosphere hypersonic flows. The new models are in good agreement with the measured Arrhenius rates for near-equilibrium conditions and with both measured rates and other theoretical models for far-from-equilibrium conditions. Additionally, the new models are applied to representative combustion and ionization reactions and are in good agreement with available measurements and theoretical models. Thus, molecular-level chemistry modeling provides an accurate method for predicting equilibrium and nonequilibrium chemical-reaction rates in gases.

Non-animal approaches for toxicokinetics in risk evaluations of food chemicals.

Science.gov (United States)

Punt, Ans; Peijnenburg, Ad A C M; Hoogenboom, Ron L A P; Bouwmeester, Hans

2017-01-01

The objective of the present work was to review the availability and predictive value of non-animal toxicokinetic approaches and to evaluate their current use in European risk evaluations of food contaminants, additives and food contact materials, as well as pesticides and medicines. Results revealed little use of quantitative animal or human kinetic data in risk evaluations of food chemicals, compared with pesticides and medicines. Risk evaluations of medicines provided sufficient in vivo kinetic data from different species to evaluate the predictive value of animal kinetic data for humans. These data showed a relatively poor correlation between the in vivo bioavailability in rats and dogs versus that in humans. In contrast, in vitro (human) kinetic data have been demonstrated to provide adequate predictions of the fate of compounds in humans, using appropriate in vitro-in vivo scalers and by integration of in vitro kinetic data with in silico kinetic modelling. Even though in vitro kinetic data were found to be occasionally included within risk evaluations of food chemicals, particularly results from Caco-2 absorption experiments and in vitro data on gut-microbial conversions, only minor use of in vitro methods for metabolism and quantitative in vitro-in vivo extrapolation methods was identified. Yet, such quantitative predictions are essential in the development of alternatives to animal testing as well as to increase human relevance of toxicological risk evaluations. Future research should aim at further improving and validating quantitative alternative methods for kinetics, thereby increasing regulatory acceptance of non-animal kinetic data.

Domino effects within a chemical cluster : A game-theoretical modeling approach by using Nash-equilibrium

NARCIS (Netherlands)

Reniers, Genserik; Dullaert, Wout; Karel, Soudan

2009-01-01

Every company situated within a chemical cluster faces domino effect risks, whose magnitude depends on every company's own risk management strategies and on those of all others. Preventing domino effects is therefore very important to avoid catastrophes in the chemical process industry. Given that

Extent of hydrogen coverage of Si(001) under chemical vapor deposition conditions from ab initio approaches

International Nuclear Information System (INIS)

Rosenow, Phil; Tonner, Ralf

2016-01-01

The extent of hydrogen coverage of the Si(001) c(4 × 2) surface in the presence of hydrogen gas has been studied with dispersion corrected density functional theory. Electronic energy contributions are well described using a hybrid functional. The temperature dependence of the coverage in thermodynamic equilibrium was studied computing the phonon spectrum in a supercell approach. As an approximation to these demanding computations, an interpolated phonon approach was found to give comparable accuracy. The simpler ab initio thermodynamic approach is not accurate enough for the system studied, even if corrections by the Einstein model for surface vibrations are considered. The on-set of H 2 desorption from the fully hydrogenated surface is predicted to occur at temperatures around 750 K. Strong changes in hydrogen coverage are found between 1000 and 1200 K in good agreement with previous reflectance anisotropy spectroscopy experiments. These findings allow a rational choice for the surface state in the computational treatment of chemical reactions under typical metal organic vapor phase epitaxy conditions on Si(001).

Extent of hydrogen coverage of Si(001) under chemical vapor deposition conditions from ab initio approaches

Energy Technology Data Exchange (ETDEWEB)

Rosenow, Phil; Tonner, Ralf, E-mail: tonner@chemie.uni-marburg.de [Fachbereich Chemie and Wissenschaftliches Zentrum für Materialwissenschaften, Philipps-Universität Marburg, Hans-Meerwein-Straße, Marburg 35032 (Germany)

2016-05-28

The extent of hydrogen coverage of the Si(001) c(4 × 2) surface in the presence of hydrogen gas has been studied with dispersion corrected density functional theory. Electronic energy contributions are well described using a hybrid functional. The temperature dependence of the coverage in thermodynamic equilibrium was studied computing the phonon spectrum in a supercell approach. As an approximation to these demanding computations, an interpolated phonon approach was found to give comparable accuracy. The simpler ab initio thermodynamic approach is not accurate enough for the system studied, even if corrections by the Einstein model for surface vibrations are considered. The on-set of H{sub 2} desorption from the fully hydrogenated surface is predicted to occur at temperatures around 750 K. Strong changes in hydrogen coverage are found between 1000 and 1200 K in good agreement with previous reflectance anisotropy spectroscopy experiments. These findings allow a rational choice for the surface state in the computational treatment of chemical reactions under typical metal organic vapor phase epitaxy conditions on Si(001).

Extent of hydrogen coverage of Si(001) under chemical vapor deposition conditions from ab initio approaches

Science.gov (United States)

Rosenow, Phil; Tonner, Ralf

2016-05-01

The extent of hydrogen coverage of the Si(001) c(4 × 2) surface in the presence of hydrogen gas has been studied with dispersion corrected density functional theory. Electronic energy contributions are well described using a hybrid functional. The temperature dependence of the coverage in thermodynamic equilibrium was studied computing the phonon spectrum in a supercell approach. As an approximation to these demanding computations, an interpolated phonon approach was found to give comparable accuracy. The simpler ab initio thermodynamic approach is not accurate enough for the system studied, even if corrections by the Einstein model for surface vibrations are considered. The on-set of H2 desorption from the fully hydrogenated surface is predicted to occur at temperatures around 750 K. Strong changes in hydrogen coverage are found between 1000 and 1200 K in good agreement with previous reflectance anisotropy spectroscopy experiments. These findings allow a rational choice for the surface state in the computational treatment of chemical reactions under typical metal organic vapor phase epitaxy conditions on Si(001).

Controlling organic chemical hazards in food manufacturing: a hazard analysis critical control points (HACCP) approach.

Science.gov (United States)

Ropkins, K; Beck, A J

2002-08-01

Hazard analysis by critical control points (HACCP) is a systematic approach to the identification, assessment and control of hazards. Effective HACCP requires the consideration of all hazards, i.e., chemical, microbiological and physical. However, to-date most 'in-place' HACCP procedures have tended to focus on the control of microbiological and physical food hazards. In general, the chemical component of HACCP procedures is either ignored or limited to applied chemicals, e.g., food additives and pesticides. In this paper we discuss the application of HACCP to a broader range of chemical hazards, using organic chemical contaminants as examples, and the problems that are likely to arise in the food manufacturing sector. Chemical HACCP procedures are likely to result in many of the advantages previously identified for microbiological HACCP procedures: more effective, efficient and economical than conventional end-point-testing methods. However, the high costs of analytical monitoring of chemical contaminants and a limited understanding of formulation and process optimisation as means of controlling chemical contamination of foods are likely to prevent chemical HACCP becoming as effective as microbiological HACCP.

Automated Physico-Chemical Cell Model Development through Information Theory

Energy Technology Data Exchange (ETDEWEB)

Peter J. Ortoleva

2005-11-29

The objective of this project was to develop predictive models of the chemical responses of microbial cells to variations in their surroundings. The application of these models is optimization of environmental remediation and energy-producing biotechnical processes.The principles on which our project is based are as follows: chemical thermodynamics and kinetics; automation of calibration through information theory; integration of multiplex data (e.g. cDNA microarrays, NMR, proteomics), cell modeling, and bifurcation theory to overcome cellular complexity; and the use of multiplex data and information theory to calibrate and run an incomplete model. In this report we review four papers summarizing key findings and a web-enabled, multiple module workflow we have implemented that consists of a set of interoperable systems biology computational modules.

Identification of Chemical Reactor Plant’s Mathematical Model

Directory of Open Access Journals (Sweden)

Pyakillya Boris

2015-01-01

Full Text Available This work presents a solution of the identification problem of chemical reactor plant’s mathematical model. The main goal is to obtain a mathematical description of a chemical reactor plant from experimental data, which based on plant’s time response measurements. This data consists sequence of measurements for water jacket temperature and information about control input signal, which is used to govern plant’s behavior.

Chemical Kinetic Modeling of 2-Methylhexane Combustion

KAUST Repository

Mohamed, Samah Y.

2015-03-30

Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important for investigating the combustion behavior of diesel, gasoline, and aviation fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values and rate rules. These update provides a better agreement with rapid compression machine measurements of ignition delay time, while also strengthening the fundamental basis of the model.

How to detect the location and time of a covert chemical attack a Bayesian approach

OpenAIRE

See, Mei Eng Elaine.

2009-01-01

Approved for public release, distribution unlimited In this thesis, we develop a Bayesian updating model that estimates the location and time of a chemical attack using inputs from chemical sensors and Atmospheric Threat and Dispersion (ATD) models. In bridging the critical gap between raw sensor data and threat evaluation and prediction, the model will help authorities perform better hazard prediction and damage control. The model is evaluated with respect to settings representing real-wo...

Toward a comprehensive model of chemical transport in porous media

International Nuclear Information System (INIS)

Miller, C.W.

1983-02-01

A chemical transport model, CHEMTRN, that includes advection, dispersion/diffusion, complexation, sorption, precipitation or dissolution of solids, and the dissociation of water has been written. The transport, mass action and site constraint equations are written in a differential/algebraic form and solved simultaneously. The sorption process is modelled by either ion-exchange or surface complexation. The model has been used to investigate the applicability of a k/sub D/ model for simulating the transport of chemical species in groundwater systems, to simulate precipitation/dissolution of minerals, and to consider the effect of surface complexation on sorption

Modeling of an improved chemical vapor infiltration process for ceramic composites fabrication

International Nuclear Information System (INIS)

Tai, N.H.; Chou, T.W.

1990-01-01

A quasi-steady-state approach is applied to model the pressure-driven, temperature-gradient chemical vapor infiltration (improved CVI process) for ceramic matrix composites fabrication. The deposited matrix in this study is SiC which is converted from the thermal decomposition of methyltrichlorosilane gas under excess hydrogen. A three-dimensional unit cell is adopted to simulate the spatial arrangements of reinforcements in discontinuous fiber mats and three-dimensionally woven fabrics. The objectives of this paper are to predict the temperature and density distributions in a fibrous preform during processing, the advancement of the solidified front, the total fabrication period, and the vapor inlet pressure variation for maintaining a constant flow rate

Chemical pattern of brazilian apples: a chemometric approach based on the Fuji and Gala varieties

Directory of Open Access Journals (Sweden)

Renato Giovanetti Vieira

2011-06-01

Full Text Available The chemical composition of apple juices may be used to discriminate between the varieties for consumption and those for raw material. Fuji and Gala have a chemical pattern that can be used for this classification. Multivariate methods correlate independent continuous chemical descriptors with the categorical apple variety. Three main descriptors of apple juice were selected: malic acid, total reducing sugar and total phenolic compounds. A chemometric approach, employing PCA and SIMCA, was used to classify apple juice samples. PCA was performed with 24 juices from Fuji and Gala, and SIMCA, with 15 juices. The exploratory and predictive models recognized 88% and 64%, respectively, as belonging to a mixed domain. The apple juice from commercial fruits shows a pattern related to cv. Fuji and Gala with boundaries from 0.18 to 0.389 g.100 mL-1 (malic acid, from 8.65 to 15.18 g.100 mL-1 (total reducing sugar and from 100 to 400 mg.L-1 (total phenolic compounds, but such boundaries were slightly shorter in the remaining set of commercial apple juices, specifically from 0.16 to 0.36 g.100 mL-1, from 9.25 to 15.5 g.100 mL-1 and from 180 to 606 mg.L-1 for acidity, reducing sugar and phenolic compounds, respectively, representing the acid, sweet and bitter tastes.

Influence of soil pH on the sorption of ionizable chemicals: modeling advances.

Science.gov (United States)

Franco, Antonio; Fu, Wenjing; Trapp, Stefan

2009-03-01

The soil-water distribution coefficient of ionizable chemicals (K(d)) depends on the soil acidity, mainly because the pH governs speciation. Using pH-specific K(d) values normalized to organic carbon (K(OC)) from the literature, a method was developed to estimate the K(OC) of monovalent organic acids and bases. The regression considers pH-dependent speciation and species-specific partition coefficients, calculated from the dissociation constant (pK(a)) and the octanol-water partition coefficient of the neutral molecule (log P(n)). Probably because of the lower pH near the organic colloid-water interface, the optimal pH to model dissociation was lower than the bulk soil pH. The knowledge of the soil pH allows calculation of the fractions of neutral and ionic molecules in the system, thus improving the existing regression for acids. The same approach was not successful with bases, for which the impact of pH on the total sorption is contrasting. In fact, the shortcomings of the model assumptions affect the predictive power for acids and for bases differently. We evaluated accuracy and limitations of the regressions for their use in the environmental fate assessment of ionizable chemicals.

Recent Trends in Quantum Chemical Modeling of Enzymatic Reactions.

Science.gov (United States)

Himo, Fahmi

2017-05-24

The quantum chemical cluster approach is a powerful method for investigating enzymatic reactions. Over the past two decades, a large number of highly diverse systems have been studied and a great wealth of mechanistic insight has been developed using this technique. This Perspective reviews the current status of the methodology. The latest technical developments are highlighted, and challenges are discussed. Some recent applications are presented to illustrate the capabilities and progress of this approach, and likely future directions are outlined.

Analyzing Unsaturated Flow Patterns in Fractured Rock Using an Integrated Modeling Approach

International Nuclear Information System (INIS)

Y.S. Wu; G. Lu; K. Zhang; L. Pan; G.S. Bodvarsson

2006-01-01

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems

On the physical and chemical details of alumina atomic layer deposition: A combined experimental and numerical approach

International Nuclear Information System (INIS)

Pan, Dongqing; Ma, Lulu; Xie, Yuanyuan; Yuan, Chris; Jen, Tien Chien

2015-01-01

Alumina thin film is typically studied as a model atomic layer deposition (ALD) process due to its high dielectric constant, high thermal stability, and good adhesion on various wafer surfaces. Despite extensive applications of alumina ALD in microelectronics industries, details on the physical and chemical processes are not yet well understood. ALD experiments are not able to shed adequate light on the detailed information regarding the transient ALD process. Most of current numerical approaches lack detailed surface reaction mechanisms, and their results are not well correlated with experimental observations. In this paper, the authors present a combined experimental and numerical study on the details of flow and surface reactions in alumina ALD using trimethylaluminum and water as precursors. Results obtained from experiments and simulations are compared and correlated. By experiments, growth rate on five samples under different deposition conditions is characterized. The deposition rate from numerical simulation agrees well with the experimental results. Details of precursor distributions in a full cycle of ALD are studied numerically to bridge between experimental observations and simulations. The 3D transient numerical model adopts surface reaction kinetics and mechanisms based on atomic-level studies to investigate the surface deposition process. Surface deposition is shown as a strictly self-limited process in our numerical studies. ALD is a complex strong-coupled fluid, thermal and chemical process, which is not only heavily dependent on the chemical kinetics and surface conditions but also on the flow and material distributions

Marine Derived Polysaccharides for Biomedical Applications: Chemical Modification Approaches

Directory of Open Access Journals (Sweden)

Paola Laurienzo

2008-09-01

Full Text Available Polysaccharide-based biomaterials are an emerging class in several biomedical fields such as tissue regeneration, particularly for cartilage, drug delivery devices and gelentrapment systems for the immobilization of cells. Important properties of the polysaccharides include controllable biological activity, biodegradability, and their ability to form hydrogels. Most of the polysaccharides used derive from natural sources; particularly, alginate and chitin, two polysaccharides which have an extensive history of use in medicine, pharmacy and basic sciences, and can be easily extracted from marine plants (algae kelp and crab shells, respectively. The recent rediscovery of poly-saccharidebased materials is also attributable to new synthetic routes for their chemical modification, with the aim of promoting new biological activities and/or to modify the final properties of the biomaterials for specific purposes. These synthetic strategies also involve the combination of polysaccharides with other polymers. A review of the more recent research in the field of chemical modification of alginate, chitin and its derivative chitosan is presented. Moreover, we report as case studies the results of our recent work concerning various different approaches and applications of polysaccharide-based biomaterials, such as the realization of novel composites based on calcium sulphate blended with alginate and with a chemically modified chitosan, the synthesis of novel alginate-poly(ethylene glycol copolymers and the development of a family of materials based on alginate and acrylic polymers of potential interest as drug delivery systems.

Whole system chemical geothermometry

International Nuclear Information System (INIS)

Pang Zhonghe

1999-01-01

Chemical and isotopic geothermometers are equations or models based on temperature dependent chemical reactions or isotope equilibrium fractionation reactions from which equilibrium temperatures of these reactions can be calculated. The major drawback of all the conventional geothermometry methods lies in their incapability on making a judgement on the equilibrium status of the studied systems. This review will focus on two of recent approaches in this field. Zhangzhou Geothermal Field in SE China will be used as an example to demonstrate the applications

Two Experiments to Approach the Boltzmann Factor: Chemical Reaction and Viscous Flow

Science.gov (United States)

Fazio, Claudio; Battaglia, Onofrio R.; Guastella, Ivan

2012-01-01

In this paper we discuss a pedagogical approach aimed at pointing out the role played by the Boltzmann factor in describing phenomena usually perceived as regulated by different mechanisms of functioning. Experimental results regarding some aspects of a chemical reaction and of the viscous flow of some liquids are analysed and described in terms…

Property Model-Based Chemcal Substitution and Chemical Formulation Design

DEFF Research Database (Denmark)

Jhamb, Spardha Virendra; Liang, Xiaodong; Hukkerikar, Amol Shivajirao

Chemical-based products including structured product formulations and single molecule products have proven to be a boon to mankind and have been a significant part of our economies. Our life and the changes around us cannot be imagined without the presence or involvement of chemicals. But like...... with environmentally benign chemicals. Additionally, the decisions taken during chemical product design also have an impact on the process and product performance and are influenced by company strategy, availability of market and government policies [2]. Hence, undoubtedly there is a need to develop a systematic...... [3] will also be highlighted. A set of new group contribution-based models for a number of useful properties of amino acids will be presented. Through examples on substitution of chemicals from chemical-based products from various sectors namely cosmetics and personal care, pharmaceutical and food...

Modeling Exposure to Persistent Chemicals in Hazard and Risk Assessment

Energy Technology Data Exchange (ETDEWEB)

Cowan-Ellsberry, Christina E.; McLachlan, Michael S.; Arnot, Jon A.; MacLeod, Matthew; McKone, Thomas E.; Wania, Frank

2008-11-01

Fate and exposure modeling has not thus far been explicitly used in the risk profile documents prepared to evaluate significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of POP and PBT chemicals in the environment. The goal of this paper is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include: (1) Benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk. (2) Directly estimating the exposure of the environment, biota and humans to provide information to complement measurements, or where measurements are not available or are limited. (3) To identify the key processes and chemical and/or environmental parameters that determine the exposure; thereby allowing the effective prioritization of research or measurements to improve the risk profile. (4) Predicting future time trends including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and whether the assumptions and input data are relevant in the context of the application

Determinants of job stress in chemical process industry: A factor analysis approach.

Science.gov (United States)

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

Equilibrator: Modeling Chemical Equilibria with Excel

Science.gov (United States)

Vander Griend, Douglas A.

2011-01-01

Equilibrator is a Microsoft Excel program for learning about chemical equilibria through modeling, similar in function to EQS4WIN, which is no longer supported and does not work well with newer Windows operating systems. Similar to EQS4WIN, Equilibrator allows the user to define a system with temperature, initial moles, and then either total…

Modelling Chemical Reasoning to Predict and Invent Reactions.

Science.gov (United States)

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model reduction of multiscale chemical langevin equations: a numerical case study.

Science.gov (United States)

Sotiropoulos, Vassilios; Contou-Carrere, Marie-Nathalie; Daoutidis, Prodromos; Kaznessis, Yiannis N

2009-01-01

Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models. Second, models must take into consideration the disparate spectrum of time scales observed in biological phenomena, such as slow transcription events and fast dimerization reactions. In the last decade, significant efforts have been expended on the development of stochastic chemical kinetics models to capture the dynamics of biomolecular systems, and on the development of robust multiscale algorithms, able to handle stiffness. In this paper, the focus is on the dynamics of reaction sets governed by stiff chemical Langevin equations, i.e., stiff stochastic differential equations. These are particularly challenging systems to model, requiring prohibitively small integration step sizes. We describe and illustrate the application of a semianalytical reduction framework for chemical Langevin equations that results in significant gains in computational cost.

An Alternative Educational Approach for an Inorganic Chemistry Laboratory Course in Industrial and Chemical Engineering

Science.gov (United States)

Garces, Andres; Sanchez-Barba, Luis Fernando

2011-01-01

We describe an alternative educational approach for an inorganic chemistry laboratory module named "Experimentation in Chemistry", which is included in Industrial Engineering and Chemical Engineering courses. The main aims of the new approach were to reduce the high levels of failure and dropout on the module and to make the content match the…

A wet-chemical approach to perovskite and fluorite-type nanoceramics: synthesis and processing

NARCIS (Netherlands)

Veldhuis, Sjoerd

2015-01-01

In thesis the low-temperature, wet-chemical approach to various functional inorganic oxide materials is described. The main focus of this research is to control the material’s synthesis from liquid precursor to metal oxide powder or thin film; while understanding its formation mechanism. In

Laboratory evaluation of the in situ chemical treatment approach to soil and groundwater remediation

International Nuclear Information System (INIS)

Thorton, E.C.; Trader, D.E.

1993-10-01

Results of initial proof of principle laboratory testing activities successfully demonstrated the viability of the in situ chemical treatment approach for remediation of soil and groundwater contaminated by hexavalent chromium. Testing activities currently in progress further indicate that soils contaminated with hexavalent chromium and uranium at concentrations of several hundred parts per million can be successfully treated with 100 ppM hydrogen sulfide gas mixtures. Greater than 90% immobilization of hexavalent chromium and 50% immobilization of uranium have been achieved in these tests after a treatment period of one day. Activities associated with further development and implementation of the in situ chemical treatment approach include conducting additional bench scale tests with contaminated geomedia, and undertaking scale-up laboratory tests and a field demonstration. This report discusses the testing and further development of this process

Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

Science.gov (United States)

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

Chemical transport in a fissured rock: verification of a numerical model

International Nuclear Information System (INIS)

Rasmuson, A.; Narasimham, T.N.; Neretnieks.

1982-01-01

Due to the very long-term, high toxicity of some nuclear waste products, models are required to predict, in certain cases, the spatial and temporal distribution of chemical concentration less than 0.001% of the concentration released from the repository. A numerical model, TRUMP, which solves the advective diffusion equation in general three dimensions, with or without decay and source term has been verified. The method is based on an integrated finite difference approach. The studies show that as long as the magnitude of advectance is equal to or less than that of conductance for the closed surface bonding any volume element in the region (that is, numerical Peclet number -3 % or less. The realistic input parameters used in the sample calculations suggest that such a range of Peclet numbers is indeed likely to characterize deep groundwater systems in granitic and ancient argillaceous systems. A sensitivity analysis based on the errors in prediction introduced due to uncertainties in input parameters are likely to be larger than the computational inaccuracies introduced by the numerical model. Currently, a disadvantage in the TRUMP model is that the iterative method of solving the set of simultaneous equations is rather slow when time constants vary widely over the flow region. Although the iterative solution may be very desirable for large three-dimensional problems in order to minimize computer storage, it seems desirable to use a direct solver technique in conjunction with the mixed explicit-implicit approach whenever possible. Work in this direction is in progress

Modelling an industrial anaerobic granular reactor using a multi-scale approach

DEFF Research Database (Denmark)

Feldman, Hannah; Flores Alsina, Xavier; Ramin, Pedram

2017-01-01

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within...... the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark...... simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally...

Graphene growth process modeling: a physical-statistical approach

Science.gov (United States)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

Property Modelling for Applications in Chemical Product and Process Design

DEFF Research Database (Denmark)

Gani, Rafiqul

such as database, property model library, model parameter regression, and, property-model based product-process design will be presented. The database contains pure component and mixture data for a wide range of organic chemicals. The property models are based on the combined group contribution and atom...... is missing, the atom connectivity based model is employed to predict the missing group interaction. In this way, a wide application range of the property modeling tool is ensured. Based on the property models, targeted computer-aided techniques have been developed for design and analysis of organic chemicals......, polymers, mixtures as well as separation processes. The presentation will highlight the framework (ICAS software) for property modeling, the property models and issues such as prediction accuracy, flexibility, maintenance and updating of the database. Also, application issues related to the use of property...

Modeling Chemical Interaction Profiles: I. Spectral Data-Activity Relationship and Structure-Activity Relationship Models for Inhibitors and Non-inhibitors of Cytochrome P450 CYP3A4 and CYP2D6 Isozymes

Directory of Open Access Journals (Sweden)

Richard D. Beger

2012-03-01

Full Text Available An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals—drugs, pesticides, and environmental pollutants—interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP enzymes. In the present work, spectral data-activity relationship (SDAR and structure-activity relationship (SAR approaches were used to develop machine-learning classifiers of inhibitors and non-inhibitors of the CYP3A4 and CYP2D6 isozymes. The models were built upon 602 reference pharmaceutical compounds whose interactions have been deduced from clinical data, and 100 additional chemicals that were used to evaluate model performance in an external validation (EV test. SDAR is an innovative modeling approach that relies on discriminant analysis applied to binned nuclear magnetic resonance (NMR spectral descriptors. In the present work, both 1D 13C and 1D 15N-NMR spectra were used together in a novel implementation of the SDAR technique. It was found that increasing the binning size of 1D 13C-NMR and 15N-NMR spectra caused an increase in the tenfold cross-validation (CV performance in terms of both the rate of correct classification and sensitivity. The results of SDAR modeling were verified using SAR. For SAR modeling, a decision forest approach involving from 6 to 17 Mold2 descriptors in a tree was used. Average rates of correct classification of SDAR and SAR models in a hundred CV tests were 60% and 61% for CYP3A4, and 62% and 70% for CYP2D6, respectively. The rates of correct classification of SDAR and SAR models in the EV test were 73% and 86% for CYP3A4, and 76% and 90% for CYP2D6, respectively. Thus, both SDAR and SAR methods demonstrated a comparable performance in modeling a large set of structurally diverse data. Based on unique NMR structural descriptors, the new SDAR modeling method complements the existing SAR

Genetic k-means clustering approach for mapping human vulnerability to chemical hazards in the industrialized city: a case study of Shanghai, China.

Science.gov (United States)

Shi, Weifang; Zeng, Weihua

2013-06-20

Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster.

Genetic k-Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China

Directory of Open Access Journals (Sweden)

Weihua Zeng

2013-06-01

Full Text Available Reducing human vulnerability to chemical hazards in the industrialized city is a matter of great urgency. Vulnerability mapping is an alternative approach for providing vulnerability-reducing interventions in a region. This study presents a method for mapping human vulnerability to chemical hazards by using clustering analysis for effective vulnerability reduction. Taking the city of Shanghai as the study area, we measure human exposure to chemical hazards by using the proximity model with additionally considering the toxicity of hazardous substances, and capture the sensitivity and coping capacity with corresponding indicators. We perform an improved k-means clustering approach on the basis of genetic algorithm by using a 500 m × 500 m geographical grid as basic spatial unit. The sum of squared errors and silhouette coefficient are combined to measure the quality of clustering and to determine the optimal clustering number. Clustering result reveals a set of six typical human vulnerability patterns that show distinct vulnerability dimension combinations. The vulnerability mapping of the study area reflects cluster-specific vulnerability characteristics and their spatial distribution. Finally, we suggest specific points that can provide new insights in rationally allocating the limited funds for the vulnerability reduction of each cluster.

Evaluating model performance of an ensemble-based chemical data assimilation system during INTEX-B field mission

Directory of Open Access Journals (Sweden)

A. F. Arellano Jr.

2007-11-01

Full Text Available We present a global chemical data assimilation system using a global atmosphere model, the Community Atmosphere Model (CAM3 with simplified chemistry and the Data Assimilation Research Testbed (DART assimilation package. DART is a community software facility for assimilation studies using the ensemble Kalman filter approach. Here, we apply the assimilation system to constrain global tropospheric carbon monoxide (CO by assimilating meteorological observations of temperature and horizontal wind velocity and satellite CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT satellite instrument. We verify the system performance using independent CO observations taken on board the NSF/NCAR C-130 and NASA DC-8 aircrafts during the April 2006 part of the Intercontinental Chemical Transport Experiment (INTEX-B. Our evaluations show that MOPITT data assimilation provides significant improvements in terms of capturing the observed CO variability relative to no MOPITT assimilation (i.e. the correlation improves from 0.62 to 0.71, significant at 99% confidence. The assimilation provides evidence of median CO loading of about 150 ppbv at 700 hPa over the NE Pacific during April 2006. This is marginally higher than the modeled CO with no MOPITT assimilation (~140 ppbv. Our ensemble-based estimates of model uncertainty also show model overprediction over the source region (i.e. China and underprediction over the NE Pacific, suggesting model errors that cannot be readily explained by emissions alone. These results have important implications for improving regional chemical forecasts and for inverse modeling of CO sources and further demonstrate the utility of the assimilation system in comparing non-coincident measurements, e.g. comparing satellite retrievals of CO with in-situ aircraft measurements.

Enhancing the design of in situ chemical barriers with multicomponent reactive transport modeling

International Nuclear Information System (INIS)

Sevougian, S.D.; Steefel, C.I.; Yabusaki, S.B.

1994-11-01

This paper addresses the need for systematic control of field-scale performance in the emplacement and operation of in situ chemical treatment barriers; in particular, it addresses the issue of how the local coupling of reaction kinetics and material heterogeneities at the laboratory or bench scale can be accurately upscaled to the field. The authors have recently developed modeling analysis tools that can explicitly account for all relevant chemical reactions that accompany the transport of reagents and contaminants through a chemically and physically heterogeneous subsurface rock or soil matrix. These tools are incorporated into an enhanced design methodology for in situ chemical treatment technologies, and the new methodology is demonstrated in the ongoing design of a field experiment for the In Situ Redox Manipulation (ISRM) project at the U.S. Department of Energy (DOE) Hanford Site. The ISRM design approach, which systematically integrates bench-scale and site characterization information, provides an ideal test for the new reactive transport techniques. The need for the enhanced chemistry capability is demonstrated by an example that shows how intra-aqueous redox kinetics can affect the transport of reactive solutes. Simulations are carried out on massively parallel computer architectures to resolve the influence of multiscale heterogeneities on multicomponent, multidimensional reactive transport. The technology will soon be available to design larger-scale remediation schemes

Air quality modeling: evaluation of chemical and meteorological parameterizations

International Nuclear Information System (INIS)

Kim, Youngseob

2011-01-01

The influence of chemical mechanisms and meteorological parameterizations on pollutant concentrations calculated with an air quality model is studied. The influence of the differences between two gas-phase chemical mechanisms on the formation of ozone and aerosols in Europe is low on average. For ozone, the large local differences are mainly due to the uncertainty associated with the kinetics of nitrogen monoxide (NO) oxidation reactions on the one hand and the representation of different pathways for the oxidation of aromatic compounds on the other hand. The aerosol concentrations are mainly influenced by the selection of all major precursors of secondary aerosols and the explicit treatment of chemical regimes corresponding to the nitrogen oxides (NO x ) levels. The influence of the meteorological parameterizations on the concentrations of aerosols and their vertical distribution is evaluated over the Paris region in France by comparison to lidar data. The influence of the parameterization of the dynamics in the atmospheric boundary layer is important; however, it is the use of an urban canopy model that improves significantly the modeling of the pollutant vertical distribution (author) [fr

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors.

Science.gov (United States)

Huang, Hongtai; Wang, Aolin; Morello-Frosch, Rachel; Lam, Juleen; Sirota, Marina; Padula, Amy; Woodruff, Tracey J

2018-03-01

The goal of this review is to identify cumulative modeling methods used to evaluate combined effects of exposures to environmental chemicals and social stressors. The specific review question is: What are the existing quantitative methods used to examine the cumulative impacts of exposures to environmental chemical and social stressors on health? There has been an increase in literature that evaluates combined effects of exposures to environmental chemicals and social stressors on health using regression models; very few studies applied other data mining and machine learning techniques to this problem. The majority of studies we identified used regression models to evaluate combined effects of multiple environmental and social stressors. With proper study design and appropriate modeling assumptions, additional data mining methods may be useful to examine combined effects of environmental and social stressors.

Bayesian inference of chemical kinetic models from proposed reactions

KAUST Repository

Galagali, Nikhil; Marzouk, Youssef M.

2015-01-01

© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model

Quantum chemical modeling of enzymatic reactions: the case of histone lysine methyltransferase.

Science.gov (United States)

Georgieva, Polina; Himo, Fahmi

2010-06-01

Quantum chemical cluster models of enzyme active sites are today an important and powerful tool in the study of various aspects of enzymatic reactivity. This methodology has been applied to a wide spectrum of reactions and many important mechanistic problems have been solved. Herein, we report a systematic study of the reaction mechanism of the histone lysine methyltransferase (HKMT) SET7/9 enzyme, which catalyzes the methylation of the N-terminal histone tail of the chromatin structure. In this study, HKMT SET7/9 serves as a representative case to examine the modeling approach for the important class of methyl transfer enzymes. Active site models of different sizes are used to evaluate the methodology. In particular, the dependence of the calculated energies on the model size, the influence of the dielectric medium, and the particular choice of the dielectric constant are discussed. In addition, we examine the validity of some technical aspects, such as geometry optimization in solvent or with a large basis set, and the use of different density functional methods. Copyright 2010 Wiley Periodicals, Inc.

Dynamic Processes of Conceptual Change: Analysis of Constructing Mental Models of Chemical Equilibrium.

Science.gov (United States)

Chiu, Mei-Hung; Chou, Chin-Cheng; Liu, Chia-Ju

2002-01-01

Investigates students' mental models of chemical equilibrium using dynamic science assessments. Reports that students at various levels have misconceptions about chemical equilibrium. Involves 10th grade students (n=30) in the study doing a series of hands-on chemical experiments. Focuses on the process of constructing mental models, dynamic…

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era.

Science.gov (United States)

Chiu, Weihsueh A; Euling, Susan Y; Scott, Cheryl Siegel; Subramaniam, Ravi P

2013-09-15

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes. Published by Elsevier Inc.

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era

Energy Technology Data Exchange (ETDEWEB)

Chiu, Weihsueh A., E-mail: chiu.weihsueh@epa.gov [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Washington DC, 20460 (United States); Euling, Susan Y.; Scott, Cheryl Siegel; Subramaniam, Ravi P. [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Washington DC, 20460 (United States)

2013-09-15

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA) — i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on “augmentation” of weight of evidence — using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards “integration” of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for “expansion” of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual “reorientation” of QRA towards approaches that more directly link environmental exposures to human outcomes.

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era

International Nuclear Information System (INIS)

Chiu, Weihsueh A.; Euling, Susan Y.; Scott, Cheryl Siegel; Subramaniam, Ravi P.

2013-01-01

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA) — i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on “augmentation” of weight of evidence — using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards “integration” of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for “expansion” of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual “reorientation” of QRA towards approaches that more directly link environmental exposures to human outcomes

Simplified Thermo-Chemical Modelling For Hypersonic Flow

Science.gov (United States)

Sancho, Jorge; Alvarez, Paula; Gonzalez, Ezequiel; Rodriguez, Manuel

2011-05-01

Hypersonic flows are connected with high temperatures, generally associated with strong shock waves that appear in such flows. At high temperatures vibrational degrees of freedom of the molecules may become excited, the molecules may dissociate into atoms, the molecules or free atoms may ionize, and molecular or ionic species, unimportant at lower temperatures, may be formed. In order to take into account these effects, a chemical model is needed, but this model should be simplified in order to be handled by a CFD code, but with a sufficient precision to take into account the physics more important. This work is related to a chemical non-equilibrium model validation, implemented into a commercial CFD code, in order to obtain the flow field around bodies in hypersonic flow. The selected non-equilibrium model is composed of seven species and six direct reactions together with their inverse. The commercial CFD code where the non- equilibrium model has been implemented is FLUENT. For the validation, the X38/Sphynx Mach 20 case is rebuilt on a reduced geometry, including the 1/3 Lref forebody. This case has been run in laminar regime, non catalytic wall and with radiative equilibrium wall temperature. The validated non-equilibrium model is applied to the EXPERT (European Experimental Re-entry Test-bed) vehicle at a specified trajectory point (Mach number 14). This case has been run also in laminar regime, non catalytic wall and with radiative equilibrium wall temperature.

Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine

Directory of Open Access Journals (Sweden)

Alexios eKoutsoukas

2016-03-01

Full Text Available Modern drug discovery and toxicological research are under pressure, as the cost of developing and testing new chemicals for potential toxicological risk is rising. Extensive evaluation of chemical products for potential adverse effects is a challenging task, due to the large number of chemicals and the possible hazardous effects on human health. Safety regulatory agencies around the world are dealing with two major challenges. First, the growth of chemicals introduced every year in household products and medicines that need to be tested, and second the need to protect public welfare. Hence, alternative and more efficient toxicological risk assessment methods are in high demand. The Toxicology in the 21st Century (Tox21 consortium a collaborative effort was formed to develop and investigate alternative assessment methods. A collection of 10,000 compounds composed of environmental chemicals and approved drugs were screened for interference in biochemical pathways and released for crowdsourcing data analysis. The physicochemical space covered by Tox21 library was explored, measured by Molecular Weight (MW and the octanol/water partition coefficient (cLogP. It was found that on average chemical structures had MW of 272.6 Daltons. In case of cLogP the average value was 2.476. Next relationships between assays were examined based on compounds activity profiles across the assays utilizing the Pearson correlation coefficient r. A cluster was observed between the Androgen and Estrogen Receptors and their ligand bind domains accordingly indicating presence of cross talks among the receptors. The highest correlations observed were between NR.AR and NR.AR_LBD, where it was r=0.66 and between NR.ER and NR.ER_LBD, where it was r=0.5.Our approach to model the Tox21 data consisted of utilizing circular molecular fingerprints combined with Random Forest and Support Vector Machine by modeling each assay independently. In all of the 12 sub-challenges our modeling

Molecular modeling for the design of novel performance chemicals and materials

CERN Document Server

Rai, Beena

2012-01-01

Molecular modeling (MM) tools offer significant benefits in the design of industrial chemical plants and material processing operations. While the role of MM in biological fields is well established, in most cases MM works as an accessory in novel products/materials development rather than a tool for direct innovation. As a result, MM engineers and practitioners are often seized with the question: ""How do I leverage these tools to develop novel materials or chemicals in my industry?"" Molecular Modeling for the Design of Novel Performance Chemicals and Materials answers this important questio

Quantum-Chemical Approach to NMR Chemical Shifts in Paramagnetic Solids Applied to LiFePO4 and LiCoPO4.

Science.gov (United States)

Mondal, Arobendo; Kaupp, Martin

2018-04-05

A novel protocol to compute and analyze NMR chemical shifts for extended paramagnetic solids, accounting comprehensively for Fermi-contact (FC), pseudocontact (PC), and orbital shifts, is reported and applied to the important lithium ion battery cathode materials LiFePO 4 and LiCoPO 4 . Using an EPR-parameter-based ansatz, the approach combines periodic (hybrid) DFT computation of hyperfine and orbital-shielding tensors with an incremental cluster model for g- and zero-field-splitting (ZFS) D-tensors. The cluster model allows the use of advanced multireference wave function methods (such as CASSCF or NEVPT2). Application of this protocol shows that the 7 Li shifts in the high-voltage cathode material LiCoPO 4 are dominated by spin-orbit-induced PC contributions, in contrast with previous assumptions, fundamentally changing interpretations of the shifts in terms of covalency. PC contributions are smaller for the 7 Li shifts of the related LiFePO 4 , where FC and orbital shifts dominate. The 31 P shifts of both materials finally are almost pure FC shifts. Nevertheless, large ZFS contributions can give rise to non-Curie temperature dependences for both 7 Li and 31 P shifts.

The Kimball Free-Cloud Model: A Failed Innovation in Chemical Education?

Science.gov (United States)

Jensen, William B.

2014-01-01

This historical review traces the origins of the Kimball free-cloud model of the chemical bond, otherwise known as the charge-cloud or tangent-sphere model, and the central role it played in attempts to reform the introductory chemical curriculum at both the high school and college levels in the 1960s. It also critically evaluates the limitations…

CarcinoPred-EL: Novel models for predicting the carcinogenicity of chemicals using molecular fingerprints and ensemble learning methods.

Science.gov (United States)

Zhang, Li; Ai, Haixin; Chen, Wen; Yin, Zimo; Hu, Huan; Zhu, Junfeng; Zhao, Jian; Zhao, Qi; Liu, Hongsheng

2017-05-18

Carcinogenicity refers to a highly toxic end point of certain chemicals, and has become an important issue in the drug development process. In this study, three novel ensemble classification models, namely Ensemble SVM, Ensemble RF, and Ensemble XGBoost, were developed to predict carcinogenicity of chemicals using seven types of molecular fingerprints and three machine learning methods based on a dataset containing 1003 diverse compounds with rat carcinogenicity. Among these three models, Ensemble XGBoost is found to be the best, giving an average accuracy of 70.1 ± 2.9%, sensitivity of 67.0 ± 5.0%, and specificity of 73.1 ± 4.4% in five-fold cross-validation and an accuracy of 70.0%, sensitivity of 65.2%, and specificity of 76.5% in external validation. In comparison with some recent methods, the ensemble models outperform some machine learning-based approaches and yield equal accuracy and higher specificity but lower sensitivity than rule-based expert systems. It is also found that the ensemble models could be further improved if more data were available. As an application, the ensemble models are employed to discover potential carcinogens in the DrugBank database. The results indicate that the proposed models are helpful in predicting the carcinogenicity of chemicals. A web server called CarcinoPred-EL has been built for these models ( http://ccsipb.lnu.edu.cn/toxicity/CarcinoPred-EL/ ).

The multi-flavor Schwinger model with chemical potential. Overcoming the sign problem with matrix product states

International Nuclear Information System (INIS)

Banuls, Mari Carmen; Cirac, J. Ignacio; Kuehn, Stefan; Cichy, Krzysztof

2016-11-01

During recent years there has been an increasing interest in the application of matrix product states, and more generally tensor networks, to lattice gauge theories. This non-perturbative method is sign problem free and has already been successfully used to compute mass spectra, thermal states and phase diagrams, as well as real-time dynamics for Abelian and non-Abelian gauge models. In previous work we showed the suitability of the method to explore the zero-temperature phase structure of the multi-flavor Schwinger model at non-zero chemical potential, a regime where the conventional Monte Carlo approach suffers from the sign problem. Here we extend our numerical study by looking at the spatially resolved chiral condensate in the massless case. We recover spatial oscillations, similar to the theoretical predictions for the single-flavor case, with a chemical potential dependent frequency and an amplitude approximately given by the homogeneous zero density condensate value.

The multi-flavor Schwinger model with chemical potential. Overcoming the sign problem with matrix product states

Energy Technology Data Exchange (ETDEWEB)

Banuls, Mari Carmen; Cirac, J. Ignacio; Kuehn, Stefan [Max-Planck-Institut fuer Quantenoptik (MPQ), Garching (Germany); Cichy, Krzysztof [Frankfurt Univ. (Germany). Inst. fuer Theoretische Physik; Adam Mickiewicz Univ., Poznan (Poland). Faculty of Physics; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Saito, Hana [AISIN AW Co., Ltd., Aichi (Japan)

2016-11-15

During recent years there has been an increasing interest in the application of matrix product states, and more generally tensor networks, to lattice gauge theories. This non-perturbative method is sign problem free and has already been successfully used to compute mass spectra, thermal states and phase diagrams, as well as real-time dynamics for Abelian and non-Abelian gauge models. In previous work we showed the suitability of the method to explore the zero-temperature phase structure of the multi-flavor Schwinger model at non-zero chemical potential, a regime where the conventional Monte Carlo approach suffers from the sign problem. Here we extend our numerical study by looking at the spatially resolved chiral condensate in the massless case. We recover spatial oscillations, similar to the theoretical predictions for the single-flavor case, with a chemical potential dependent frequency and an amplitude approximately given by the homogeneous zero density condensate value.

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

Modeling in applied sciences a kinetic theory approach

CERN Document Server

Pulvirenti, Mario

2000-01-01

Modeling complex biological, chemical, and physical systems, in the context of spatially heterogeneous mediums, is a challenging task for scientists and engineers using traditional methods of analysis Modeling in Applied Sciences is a comprehensive survey of modeling large systems using kinetic equations, and in particular the Boltzmann equation and its generalizations An interdisciplinary group of leading authorities carefully develop the foundations of kinetic models and discuss the connections and interactions between model theories, qualitative and computational analysis and real-world applications This book provides a thoroughly accessible and lucid overview of the different aspects, models, computations, and methodology for the kinetic-theory modeling process Topics and Features * Integrated modeling perspective utilized in all chapters * Fluid dynamics of reacting gases * Self-contained introduction to kinetic models * Becker–Doring equations * Nonlinear kinetic models with chemical reactions * Kinet...

Analysis of Chemical Bioactivity through In Vitro Profiling ...

Science.gov (United States)

Safety assessment of drugs and environmental chemicals relies extensively on animal testing. However, the quantity of chemicals needing assessment and challenges of species extrapolation drive the development of alternative approaches. The EPA’s ToxCast and the multiagency Tox21 programs address this through use of an extensive in vitro screening program to generate data on a large library of important environmental chemicals. These in vitro assays encompass both cell-free, biochemical assays targeting proteins that may be potential molecular initiating events and cellular assays that provide coverage of critical signaling pathways and toxicity phenotypes. Effects on model organisms such as the developing zebrafish, are also part of the testing strategy. A variety of computational approaches are used to analyze the resulting complex data sets to gain insight in to inherent biological activity of chemicals and possible mechanisms of toxicity. Several case studies including identification of modulators of estrogen receptor and aromatic hydrocarbon receptor pathways with effects in primary human cell systems will be described. In addition, existing in vivo data from a subset of the chemicals was used to anchor predictive models using in vitro data for a number of adverse endpoints including reproductive and developmental toxicities. The strengths and weaknesses of this approach will be described. This work does not necessarily reflect official Agency policy. Pres

Model of wet chemical etching of swift heavy ions tracks

Science.gov (United States)

Gorbunov, S. A.; Malakhov, A. I.; Rymzhanov, R. A.; Volkov, A. E.

2017-10-01

A model of wet chemical etching of tracks of swift heavy ions (SHI) decelerated in solids in the electronic stopping regime is presented. This model takes into account both possible etching modes: etching controlled by diffusion of etchant molecules to the etching front, and etching controlled by the rate of a reaction of an etchant with a material. Olivine ((Mg0.88Fe0.12)2SiO4) crystals were chosen as a system for modeling. Two mechanisms of chemical activation of olivine around the SHI trajectory are considered. The first mechanism is activation stimulated by structural transformations in a nanometric track core, while the second one results from neutralization of metallic atoms by generated electrons spreading over micrometric distances. Monte-Carlo simulations (TREKIS code) form the basis for the description of excitations of the electronic subsystem and the lattice of olivine in an SHI track at times up to 100 fs after the projectile passage. Molecular dynamics supplies the initial conditions for modeling of lattice relaxation for longer times. These simulations enable us to estimate the effects of the chemical activation of olivine governed by both mechanisms. The developed model was applied to describe chemical activation and the etching kinetics of tracks of Au 2.1 GeV ions in olivine. The estimated lengthwise etching rate (38 µm · h-1) is in reasonable agreement with that detected in the experiments (24 µm · h-1).

Modeling exposure to persistent chemicals in hazard and risk assessment.

Science.gov (United States)

Cowan-Ellsberry, Christina E; McLachlan, Michael S; Arnot, Jon A; Macleod, Matthew; McKone, Thomas E; Wania, Frank

2009-10-01

Fate and exposure modeling has not, thus far, been explicitly used in the risk profile documents prepared for evaluating the significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of persistent organic pollutants (POP) and persistent, bioaccumulative, and toxic (PBT) chemicals in the environment. The goal of this publication is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include 1) benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk; 2) directly estimating the exposure of the environment, biota, and humans to provide information to complement measurements or where measurements are not available or are limited; 3) to identify the key processes and chemical or environmental parameters that determine the exposure, thereby allowing the effective prioritization of research or measurements to improve the risk profile; and 4) forecasting future time trends, including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and

Regression analysis of a chemical reaction fouling model

International Nuclear Information System (INIS)

Vasak, F.; Epstein, N.

1996-01-01

A previously reported mathematical model for the initial chemical reaction fouling of a heated tube is critically examined in the light of the experimental data for which it was developed. A regression analysis of the model with respect to that data shows that the reference point upon which the two adjustable parameters of the model were originally based was well chosen, albeit fortuitously. (author). 3 refs., 2 tabs., 2 figs

Protein engineering approaches to chemical biotechnology.

Science.gov (United States)

Chen, Zhen; Zeng, An-Ping

2016-12-01

Protein engineering for the improvement of properties of biocatalysts and for the generation of novel metabolic pathways plays more and more important roles in chemical biotechnology aiming at the production of chemicals from biomass. Although widely used in single-enzyme catalysis process, protein engineering is only being increasingly explored in recent years to achieve more complex in vitro and in vivo biocatalytic processes. This review focuses on major contributions of protein engineering to chemical biotechnology in the field of multi-enzymatic cascade catalysis and metabolic engineering. Especially, we discuss and highlight recent strategies for combining pathway design and protein engineering for the production of novel products. Copyright © 2016. Published by Elsevier Ltd.

Emissions model of waste treatment operations at the Idaho Chemical Processing Plant

International Nuclear Information System (INIS)

Schindler, R.E.

1995-03-01

An integrated model of the waste treatment systems at the Idaho Chemical Processing Plant (ICPP) was developed using a commercially-available process simulation software (ASPEN Plus) to calculate atmospheric emissions of hazardous chemicals for use in an application for an environmental permit to operate (PTO). The processes covered by the model are the Process Equipment Waste evaporator, High Level Liquid Waste evaporator, New Waste Calcining Facility and Liquid Effluent Treatment and Disposal facility. The processes are described along with the model and its assumptions. The model calculates emissions of NO x , CO, volatile acids, hazardous metals, and organic chemicals. Some calculated relative emissions are summarized and insights on building simulations are discussed

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

Energy Technology Data Exchange (ETDEWEB)