Guillaume Fayet

Theoretical Study of the Decomposition Reactions in Substituted Nitrobenzenes

The influence of substituent nature and position on the unimolecular decomposition of nitroaromatic compounds was investigated using the density functional theory at a PBE0/6-31+G(d,p) level. As the starting point, the two main reaction paths for the decomposition of nitrobenzene were analyzed: the direct carbon nitrogen dissociation (C6H5 + NO2) and a two step mechanism leading to the formation of phenoxyl and nitro radicals (C6H5O + NO). The dissociation energy of the former reaction was calculated to be 7.5 kcal/mol lower than the activation energy of the second reaction. Then the Gibbs free energies were computed for 15 nitrobenzene derivatives characterized by different substituents (nitro, methyl, amino, carboxylic acid, and hydroxyl) in the ortho, meta, and para positions. In meta position, no significant changes appeared in the reaction energy profiles whereas ortho and para substitutions led to significant deviations in energies on the decomposition mechanisms due to the resonance effect of the nitro group without changing the competition between these mechanisms. In the case of para and meta substitutions, the carbon-nitro bond dissociation energy has been directly related to the Hammett constant as an indicator of the electron donor-acceptor effect of substituents.

On the prediction of thermal stability of nitroaromatic compounds using quantum chemical calculations

This work presents a new approach to predict thermal stability of nitroaromatic compounds based on quantum chemical calculations and on quantitative structure-property relationship (QSPR) methods. The data set consists of 22 nitroaromatic compounds of known decomposition enthalpy (taken as a macroscopic property related to explosibility) obtained from differential scanning calorimetry. Geometric, electronic and energetic descriptors have been selected and computed using density functional theory (DFT) calculation to describe the 22 molecules. First approach consisted in looking at their linear correlations with the experimental decomposition enthalpy. Molecular weight, electrophilicity index, electron affinity and oxygen balance appeared as the most correlated descriptors (respectively R(2)=0.76, 0.75, 0.71 and 0.64). Then multilinear regression was computed with these descriptors. The obtained model is a six-parameter equation containing descriptors all issued from quantum chemical calculations. The prediction is satisfactory with a correlation coefficient R(2) of 0.91 and a predictivity coefficient R(cv)(2) of 0.84 using a cross validation method.

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

The molecular structures of 77 nitroaromatic compounds have been correlated to their thermal stabilities by combining the quantitative structure–property relationship (QSPR) method with density functional theory (DFT). More than 300 descriptors (constitutional, topological, geometrical and quantum chemical) have been calculated, and multilinear regressions have been performed to find accurate quantitative relationships with experimental heats of decomposition (−ΔH). In particular, this work demonstrates the importance of accounting for chemical mechanisms during the selection of an adequate experimental data set. A reliable QSPR model that presents a strong correlation with experimental data for both the training and the validation molecular sets (R2 = 0.90 and 0.84, respectively) was developed for non-ortho-substituted nitroaromatic compounds. Moreover, its applicability domain was determined, and the model’s predictivity reached 0.86 within this applicability domain. To our knowledge, this work has produced the first QSPR model, developed according to the OECD principles of regulatory acceptability, for predicting the thermal stabilities of energetic compounds.

A General Guidebook for the Theoretical Prediction of Physicochemical Properties of Chemicals for Regulatory Purposes

Physicochemical Properties of Chemicals for Regulatory Purposes Carlos Nieto-Draghi,*,† Guillaume Fayet,‡ Benoit Creton,† Xavier Rozanska, Patricia Rotureau,‡ Jean-Charles de Hemptinne,† Philippe Ungerer, Bernard Rousseau, and Carlo Adamo †IFP Energies nouvelles, 1 et 4 avenue de Bois-Preáu, 92852 Rueil-Malmaison, France ‡INERIS, Parc Technologique Alata, BP2, 60550 Verneuil-en-Halatte, France Materials Design S.A.R.L., 18, rue de Saisset, 92120 Montrouge, France Laboratoire de Chimie-Physique, Universite ́ Paris Sud, UMR 8000 CNRS, Bat̂. 349, 91405 Orsay Cedex, France Institut de Recherche Chimie Paris, PSL Research University, CNRS, Chimie Paristech, 11 rue P. et M. Curie, F-75005 Paris, France Institut Universitaire de France, 103 Boulevard Saint Michel, F-75005 Paris, France

QSPR modeling of thermal stability of nitroaromatic compounds: DFT vs. AM1 calculated descriptors

The quantitative structure-property relationship (QSPR) methodology was applied to predict the decomposition enthalpies of 22 nitroaromatic compounds, used as indicators of thermal stability. An extended series of descriptors (constitutional, topological, geometrical charge related and quantum chemical) was calculated at two different levels of theory: density functional theory (DFT) and semi-empirical AM1 approaches. Reliable models have been developed for each level, leading to similar correlations between calculated and experimental data (R2 > 0.98). Hence, both of them can be employed as screening tools for the prediction of thermal stability of nitroaromatic compounds. If using the AM1 model presents the advantage to be less time consuming, DFT allows the calculation of more accurate molecular quantum properties, e.g., conceptual DFT descriptors. In this study, our best QSPR model is based on such descriptors, providing more chemical comprehensive relationships with decomposition reactivity, a particularly complex property for the specific class of nitroaromatic compounds.

Predicting the thermal stability of nitroaromatic compounds using chemoinformatic tools

In the framework of the European REACH regulation major attention was recently devoted to toxicological and ecotoxicological problems while little attention has been dedicated to other important applications concerning chemical hazards, for instance, explosive properties. In this work different chemoinformatic tools such as partial least squares, multilinear regressions, and decision trees have been used for the development of a novel quantitative structure‐property relationships to predict the heat of decomposition of a series of nitroaromatic compounds. Models were conceived in order to follow the regulatory requirements according to OECD principles for the validation of QSAR methods. Three models derived with MLR, PLS and decision tree techniques were developed, validated (internally and externally) and their applicability domains have been defined and analyzed. All models proved to be reliable with remarkable robustness in terms of full cross‐validation scheme and showed good predictive power toward the external validation set. These models also present a large applicability domain within nitrobenzene derivatives and are easy to implement and interpret in terms of subjacent mechanisms.

Excited-state properties from ground-state DFT descriptors: A QSPR approach for dyes

This work presents a quantitative structure-property relationship (QSPR)-based approach allowing an accurate prediction of the excited-state properties of organic dyes (anthraquinones and azobenzenes) from ground-state molecular descriptors, obtained within the (conceptual) density functional theory (DFT) framework. The ab initio computation of the descriptors was achieved at several levels of theory, so that the influence of the basis set size as well as of the modeling of environmental effects could be statistically quantified. It turns out that, for the entire data set, a statistically-robust four-variable multiple linear regression based on PCM-PBE0/6-31G calculations delivers a R(adj)(2) of 0.93 associated to predictive errors allowing for rapid and efficient dye design. All the selected descriptors are independent of the dyes family, an advantage over previously designed QSPR schemes. On top of that, the obtained accuracy is comparable to the one of the todays reference methods while exceeding the one of hardness-based fittings. QSPR relationships specific to both families of dyes have also been built up. This work paves the way towards reliable and computationally affordable color design for organic dyes.

Predicting explosibility properties of chemicals from quantitative structure-property relationships†

Quantitative Structure‐Property Relationship (QSPR) type methods have been up to now mainly devoted to biological, toxicological applications but their use to predict physico‐chemical properties is a growing interest. In this context, an original approach associating QSPR methods and quantum chemical calculations for the prediction of chemicals explosibility properties is presented here.

Prediction of the thermal decomposition of organic peroxides by validated QSPR models

Organic peroxides are unstable chemicals which can easily decompose and may lead to explosion. Such a process can be characterized by physico-chemical parameters such as heat and temperature of decomposition, whose determination is crucial to manage related hazards. These thermal stability properties are also required within many regulatory frameworks related to chemicals in order to assess their hazardous properties. In this work, new quantitative structure-property relationships (QSPR) models were developed to predict accurately the thermal stability of organic peroxides from their molecular structure respecting the OECD guidelines for regulatory acceptability of QSPRs. Based on the acquisition of 38 reference experimental data using DSC (differential scanning calorimetry) apparatus in homogenous experimental conditions, multi-linear models were derived for the prediction of the decomposition heat and the onset temperature using different types of molecular descriptors. Models were tested by internal and external validation tests and their applicability domains were defined and analyzed. Being rigorously validated, they presented the best performances in terms of fitting, robustness and predictive power and the descriptors used in these models were linked to the peroxide bond whose breaking represents the main decomposition mechanism of organic peroxides.

Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds

The European regulation of chemicals named REACH implies the assessment of a large number of substances based on their hazardous properties. However, the complete characterization of physico-chemical, toxicological and eco-toxicological properties by experimental means is incompatible with the imposed calendar of REACH. Hence, there is a real need in evaluating the capabilities of alternative methods such as quantitative structure-property relationship (QSPR) models, notably for physico-chemical properties. In the present work, the molecular structures of 50 itroaliphatic compounds were correlated with their impact sensitivities (h(50%)) using such predictive models. More than 400 olecular descriptors (constitutional, topological, geometrical, quantum chemical) were calculated and linear and multi-linear regressions were performed to find accurate quantitative relationships with experimental impact sensitivities. Considering different sets of descriptors, four predictive models were obtained and two of them were selected for their predictive reliability. To our knowledge, these QSPR models for the impact sensitivity of nitroaliphatic compounds are the first ones being rigorously validated (both internally and externally) with defined applicability domains. They hence follow all OECD principles for regulatory acceptability of QSPRs, allowing possible application in REACH.