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Papers by Guillaume FAYET

Research paper thumbnail of Evaluation of chemicals explosive properties: from classical experimental methods to predictive methods combining statistical QSPR methodology and quantum chemistry

Research paper thumbnail of Iron bis(arylimino)pyridine precursors activated to catalyze ethylene oligomerization as studied by DFT and QSAR approaches

Journal of Molecular Structure: THEOCHEM, 2009

Research paper thumbnail of QSPR prediction of explosibility properties of chemical substances within the framework of REACH

Research paper thumbnail of Predicting explosibility properties of chemical substances from a combined DFT-QSPR approach

Research paper thumbnail of Prediction of the physico-chemical properties of nitroaromatic compounds using QSPR models

Research paper thumbnail of QSPR prediction of impact sensitivity of nitro energetic compounds

Research paper thumbnail of Prédiction des propriétés physico-chimiques dans le cadre du projet PREDIMOL

Research paper thumbnail of Quantitative structure-property relationship studies for predicting explosibility of nitroaromatic compounds

Research paper thumbnail of Development of a new QSPR based tool to predict explosibility properties of chemical substances within the framework of REACH and GHS

Research paper thumbnail of Development of predictive methods for screening explosibility properties of chemical substances

Research paper thumbnail of Prediction of physico-chemical properties in the context of the French PREDIMOL project

The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large... more The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large number of substances in order to allow their use before 2018. Taking into account the number of substances and properties, the timing, the economic costs, the feasibility at the R&D level and the risks for the manipulator, in particular for the characterization of the dangerous physico-chemical properties (explosibility, flammability), the experimental measurement of all the data is not realistic. Thus, the development of alternative predictive methods for the evaluation of the properties of substances was recommended in the framework of REACH. In this context, the French PREDIMOL (molecular modeling prediction of physico-chemical properties of products) project [1] funded by ANR (National Research Agency) has started in November 2010 for 3 years. This project is conducted by INERIS associated with several public and private partners. Its objective is to demonstrate that molecular model...

Research paper thumbnail of Predicting the physico-chemical properties of chemicals based on QSPR models

Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correl... more Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correlations between the molecular structures of chemicals and their macroscopic properties. Such methods have been up to now mainly devoted to biological, toxicological applications but their use to predict physico-chemical properties is of growing interest in recent years. In particular, in the framework of the European REACH regulation, the development of such models was recommended as an alternative to experimental tests for reasons. Moreover, such methods represent pertinent tools in screening procedures to select the best performances in any functional properties (e.g. in chemical process) or ensuring at best against hazardous properties (like flammability, explosive or oxidizing properties). To evaluate their reliability, various validation tests are realized. In particular, a robust procedure was proposed by OCDE for their validation for regulatory purpose based on five principles rela...

Research paper thumbnail of Nanomaterials Risk Assessment in the Process Industries: Evaluation and Application of Current Control Banding Methods

Nanotechnology is a rapidly growing field and industrial developments are more and more challenge... more Nanotechnology is a rapidly growing field and industrial developments are more and more challenged by potential health and safety risks pertaining to manufactured nanomaterials. This matter is far from being solved due to the current lack of reliable data addressing occupational safety as well as environmental field. In this context, the Control Banding (CB) approach appears particularly interesting to assess ESH risks associated to nanomaterials. Our study focuses more specifically on four CB methods which have been analysed in order to highlight their a priori limits and evaluate their effectiveness for perform risk assessment in the industry. Our study concludes that too conservative frameworks, multiplicity of factors and complex algorithm are critical elements that can limit the effectiveness of the tools for risk assessment in the industry.

Research paper thumbnail of Global and Local QSPR Models to Predict the Impact Sensitivity of Nitro Compounds

New quantitative structure property relationships (QSPR) have been developed to predict accuratel... more New quantitative structure property relationships (QSPR) have been developed to predict accurately the impact sensitivity of nitro compounds from their molecular structures. Such predictive approaches represent good alternative to complete experimental testing in development process or for regulatory issues (e.g. within the European REACH regulation). To achieve highly predictive models, two approaches were used to explore the whole diversity of nitro compounds included in a data set of 161 molecules. In a first step, local models, dedicated to the nitramines, nitroaliphatics and nitroaromatics, were proposed. After that, a global model was developed to be applicable for the whole range of the nitro compounds of the data set. In both cases, large series of molecular descriptors were calculated from quantum chemically calculated molecular structures and multilinear regressions were computed to correlate them with experimental impact sensitivities. All proposed models were validated f...

Research paper thumbnail of Mixture Descriptors toward the Development of Quantitative Structure–Property Relationship Models for the Flash Points of Organic Mixtures

Industrial & Engineering Chemistry Research, 2015

ABSTRACT Quantitative structure property relationships (QSPR) are increasingly used for the predi... more ABSTRACT Quantitative structure property relationships (QSPR) are increasingly used for the prediction of physico-chemical properties of pure compounds but only few were developed to predict the properties of mixtures. In this work, a series of existing and new formula were proposed to derive mixture descriptors to develop QSPR models for mixtures. These mixture descriptors were used to model the flash point of a series of 435 organic mixture compositions. Multilinear models were obtained using twelve different mathematic formulas taking into account the linear or non-linear dependences of the flash point with the concentration of each compound. The best model, issued from the newly proposed (x1d1 + x2d2)2 formula, was a four parameter model presenting good prediction capabilities (with a mean absolute error in prediction of 10.3°C) compared to existing predictive methods for both mixtures and pure compounds.

Research paper thumbnail of Combining mixing rules with QSPR models for pure chemicals to predict the flash points of binary organic liquid mixtures

Fire Safety Journal, 2015

ABSTRACT Flash point is a key property of liquids to evaluate the safety of industrial processes.... more ABSTRACT Flash point is a key property of liquids to evaluate the safety of industrial processes. Mixing rules are commonly used to calculate the flash point of liquid mixtures, but they need knowledge of the ones of pure compounds. Theoretical methods notably based on quantitative structure property relationships (QSPR) already exist to predict flash points of pure compounds. So, in this paper, direct combination of these two types of approaches was investigated to achieve predictions even when the flash points of pure compounds were unknown. Three relevant mixing rules and four QSPR models, based on simple constitutional descriptors, were considered. Based on a data set of 284 experimental data of binary mixtures extracted from literature, two reliable combinations were highlighted. The most accurate one reached an error in prediction of only 2.9 °C but needed knowledge of the boiling point and Antoine's coefficients of each component of the mixture. A new full-predictive method was in particular proposed with also a low error in prediction (4.4 °C), requiring only knowledge of the molecular structure of each pure compound and molar fraction of the mixture. Errors in each predictive method keep quite reasonable against expected accuracies of direct measurements of flash point of binary mixtures.

Research paper thumbnail of Reply to the comment on “Decomposition mechanisms of trinitroalkyl compounds: a theoretical study from aliphatic to aromatic nitro compounds” by G. Fayet, P. Rotureau, B. Minisini, Phys. Chem. Chem. Phys., 2014, 16, 6614

Phys. Chem. Chem. Phys., 2015

Research paper thumbnail of Acridine orange in a pumpkin-shaped macrocycle: Beyond solvent effects in the UV–visible spectra simulation of dyes

Journal of Molecular Structure: THEOCHEM, 2010

We present simulation of the UV–visible spectra of acridine orange, a widely used photosensitizer... more We present simulation of the UV–visible spectra of acridine orange, a widely used photosensitizer for in vivo studies due to its highly environment-dependent spectroscopic properties. This dye has been investigated both in its protonated and neutral forms, either isolated or embedded in a pumpkin-shaped macromolecular cycle (cucurbit-7-uril), using time-dependent density functional theory techniques. To model this macromolecular cycle, two strategies

Research paper thumbnail of Prediction of Physico-Chemical Properties for REACH Based on QSPR Models

Lp2013 - 14th Symposium on Loss Prevention and Safety Promotion in the Process Industries, Vols I and Ii, 2013

Research paper thumbnail of Modeling Chemical Incompatibility: Ammonium Nitrate and Sodium Salt of Dichloroisocyanuric Acid as a Case Study

Industrial & Engineering Chemistry Research, 2014

ABSTRACT The dramatic accident involving ammonium nitrate (AN) that took place at Toulouse in Sep... more ABSTRACT The dramatic accident involving ammonium nitrate (AN) that took place at Toulouse in September 2001 has once again focused attention on the hazards pertaining to chemical incompatibility in an industrial environment. To complete the experimental results, a detailed theoretical study was performed to better understand the involved mechanisms, considering the reaction between ammonium nitrate and the sodium salt of dichloroisocyanuric acid (SDIC). Starting from theoretical results obtained for the pure reactants, the gas-phase decomposition mechanism of the mixture was investigated and fully characterized by means of density functional theory (DFT) calculations. Beyond the complete characterization, in terms of intermediate structures and energies, of the decomposition pathways, the results evidenced the role of water in catalyzing the decomposition reaction, through a significant decrease of the activation energy of the rate-determining step. These results, in qualitative agreement with the calorimetric experiments, pointed out the instability of the ANSDIC wet mixture and the underpinning incompatibility mechanism between these two chemicals.

Research paper thumbnail of Evaluation of chemicals explosive properties: from classical experimental methods to predictive methods combining statistical QSPR methodology and quantum chemistry

Research paper thumbnail of Iron bis(arylimino)pyridine precursors activated to catalyze ethylene oligomerization as studied by DFT and QSAR approaches

Journal of Molecular Structure: THEOCHEM, 2009

Research paper thumbnail of QSPR prediction of explosibility properties of chemical substances within the framework of REACH

Research paper thumbnail of Predicting explosibility properties of chemical substances from a combined DFT-QSPR approach

Research paper thumbnail of Prediction of the physico-chemical properties of nitroaromatic compounds using QSPR models

Research paper thumbnail of QSPR prediction of impact sensitivity of nitro energetic compounds

Research paper thumbnail of Prédiction des propriétés physico-chimiques dans le cadre du projet PREDIMOL

Research paper thumbnail of Quantitative structure-property relationship studies for predicting explosibility of nitroaromatic compounds

Research paper thumbnail of Development of a new QSPR based tool to predict explosibility properties of chemical substances within the framework of REACH and GHS

Research paper thumbnail of Development of predictive methods for screening explosibility properties of chemical substances

Research paper thumbnail of Prediction of physico-chemical properties in the context of the French PREDIMOL project

The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large... more The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large number of substances in order to allow their use before 2018. Taking into account the number of substances and properties, the timing, the economic costs, the feasibility at the R&D level and the risks for the manipulator, in particular for the characterization of the dangerous physico-chemical properties (explosibility, flammability), the experimental measurement of all the data is not realistic. Thus, the development of alternative predictive methods for the evaluation of the properties of substances was recommended in the framework of REACH. In this context, the French PREDIMOL (molecular modeling prediction of physico-chemical properties of products) project [1] funded by ANR (National Research Agency) has started in November 2010 for 3 years. This project is conducted by INERIS associated with several public and private partners. Its objective is to demonstrate that molecular model...

Research paper thumbnail of Predicting the physico-chemical properties of chemicals based on QSPR models

Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correl... more Quantitative Structure-Property Relationship models (QSPR) are predictive methods based on correlations between the molecular structures of chemicals and their macroscopic properties. Such methods have been up to now mainly devoted to biological, toxicological applications but their use to predict physico-chemical properties is of growing interest in recent years. In particular, in the framework of the European REACH regulation, the development of such models was recommended as an alternative to experimental tests for reasons. Moreover, such methods represent pertinent tools in screening procedures to select the best performances in any functional properties (e.g. in chemical process) or ensuring at best against hazardous properties (like flammability, explosive or oxidizing properties). To evaluate their reliability, various validation tests are realized. In particular, a robust procedure was proposed by OCDE for their validation for regulatory purpose based on five principles rela...

Research paper thumbnail of Nanomaterials Risk Assessment in the Process Industries: Evaluation and Application of Current Control Banding Methods

Nanotechnology is a rapidly growing field and industrial developments are more and more challenge... more Nanotechnology is a rapidly growing field and industrial developments are more and more challenged by potential health and safety risks pertaining to manufactured nanomaterials. This matter is far from being solved due to the current lack of reliable data addressing occupational safety as well as environmental field. In this context, the Control Banding (CB) approach appears particularly interesting to assess ESH risks associated to nanomaterials. Our study focuses more specifically on four CB methods which have been analysed in order to highlight their a priori limits and evaluate their effectiveness for perform risk assessment in the industry. Our study concludes that too conservative frameworks, multiplicity of factors and complex algorithm are critical elements that can limit the effectiveness of the tools for risk assessment in the industry.

Research paper thumbnail of Global and Local QSPR Models to Predict the Impact Sensitivity of Nitro Compounds

New quantitative structure property relationships (QSPR) have been developed to predict accuratel... more New quantitative structure property relationships (QSPR) have been developed to predict accurately the impact sensitivity of nitro compounds from their molecular structures. Such predictive approaches represent good alternative to complete experimental testing in development process or for regulatory issues (e.g. within the European REACH regulation). To achieve highly predictive models, two approaches were used to explore the whole diversity of nitro compounds included in a data set of 161 molecules. In a first step, local models, dedicated to the nitramines, nitroaliphatics and nitroaromatics, were proposed. After that, a global model was developed to be applicable for the whole range of the nitro compounds of the data set. In both cases, large series of molecular descriptors were calculated from quantum chemically calculated molecular structures and multilinear regressions were computed to correlate them with experimental impact sensitivities. All proposed models were validated f...

Research paper thumbnail of Mixture Descriptors toward the Development of Quantitative Structure–Property Relationship Models for the Flash Points of Organic Mixtures

Industrial & Engineering Chemistry Research, 2015

ABSTRACT Quantitative structure property relationships (QSPR) are increasingly used for the predi... more ABSTRACT Quantitative structure property relationships (QSPR) are increasingly used for the prediction of physico-chemical properties of pure compounds but only few were developed to predict the properties of mixtures. In this work, a series of existing and new formula were proposed to derive mixture descriptors to develop QSPR models for mixtures. These mixture descriptors were used to model the flash point of a series of 435 organic mixture compositions. Multilinear models were obtained using twelve different mathematic formulas taking into account the linear or non-linear dependences of the flash point with the concentration of each compound. The best model, issued from the newly proposed (x1d1 + x2d2)2 formula, was a four parameter model presenting good prediction capabilities (with a mean absolute error in prediction of 10.3°C) compared to existing predictive methods for both mixtures and pure compounds.

Research paper thumbnail of Combining mixing rules with QSPR models for pure chemicals to predict the flash points of binary organic liquid mixtures

Fire Safety Journal, 2015

ABSTRACT Flash point is a key property of liquids to evaluate the safety of industrial processes.... more ABSTRACT Flash point is a key property of liquids to evaluate the safety of industrial processes. Mixing rules are commonly used to calculate the flash point of liquid mixtures, but they need knowledge of the ones of pure compounds. Theoretical methods notably based on quantitative structure property relationships (QSPR) already exist to predict flash points of pure compounds. So, in this paper, direct combination of these two types of approaches was investigated to achieve predictions even when the flash points of pure compounds were unknown. Three relevant mixing rules and four QSPR models, based on simple constitutional descriptors, were considered. Based on a data set of 284 experimental data of binary mixtures extracted from literature, two reliable combinations were highlighted. The most accurate one reached an error in prediction of only 2.9 °C but needed knowledge of the boiling point and Antoine's coefficients of each component of the mixture. A new full-predictive method was in particular proposed with also a low error in prediction (4.4 °C), requiring only knowledge of the molecular structure of each pure compound and molar fraction of the mixture. Errors in each predictive method keep quite reasonable against expected accuracies of direct measurements of flash point of binary mixtures.

Research paper thumbnail of Reply to the comment on “Decomposition mechanisms of trinitroalkyl compounds: a theoretical study from aliphatic to aromatic nitro compounds” by G. Fayet, P. Rotureau, B. Minisini, Phys. Chem. Chem. Phys., 2014, 16, 6614

Phys. Chem. Chem. Phys., 2015

Research paper thumbnail of Acridine orange in a pumpkin-shaped macrocycle: Beyond solvent effects in the UV–visible spectra simulation of dyes

Journal of Molecular Structure: THEOCHEM, 2010

We present simulation of the UV–visible spectra of acridine orange, a widely used photosensitizer... more We present simulation of the UV–visible spectra of acridine orange, a widely used photosensitizer for in vivo studies due to its highly environment-dependent spectroscopic properties. This dye has been investigated both in its protonated and neutral forms, either isolated or embedded in a pumpkin-shaped macromolecular cycle (cucurbit-7-uril), using time-dependent density functional theory techniques. To model this macromolecular cycle, two strategies

Research paper thumbnail of Prediction of Physico-Chemical Properties for REACH Based on QSPR Models

Lp2013 - 14th Symposium on Loss Prevention and Safety Promotion in the Process Industries, Vols I and Ii, 2013

Research paper thumbnail of Modeling Chemical Incompatibility: Ammonium Nitrate and Sodium Salt of Dichloroisocyanuric Acid as a Case Study

Industrial & Engineering Chemistry Research, 2014

ABSTRACT The dramatic accident involving ammonium nitrate (AN) that took place at Toulouse in Sep... more ABSTRACT The dramatic accident involving ammonium nitrate (AN) that took place at Toulouse in September 2001 has once again focused attention on the hazards pertaining to chemical incompatibility in an industrial environment. To complete the experimental results, a detailed theoretical study was performed to better understand the involved mechanisms, considering the reaction between ammonium nitrate and the sodium salt of dichloroisocyanuric acid (SDIC). Starting from theoretical results obtained for the pure reactants, the gas-phase decomposition mechanism of the mixture was investigated and fully characterized by means of density functional theory (DFT) calculations. Beyond the complete characterization, in terms of intermediate structures and energies, of the decomposition pathways, the results evidenced the role of water in catalyzing the decomposition reaction, through a significant decrease of the activation energy of the rate-determining step. These results, in qualitative agreement with the calorimetric experiments, pointed out the instability of the ANSDIC wet mixture and the underpinning incompatibility mechanism between these two chemicals.