Chemoinformatics for the Safety of Energetic and Reactive Materials at Ineris.

The characterization of physical hazards of substances is a key information to manage the risks associated to their use, storage and transport. With decades of work in this area, Ineris develops and implements cutting-edge experimental facilities allowing such characterizations at different scales and under various conditions to study all of the dreaded accident scenarios. This review presents the efforts engaged by Ineris more recently in the field of chemoinformatics to develop and use new predictive methods for the anticipation and management of industrials risks associated to energetic and reactive materials as a complement to experiments. An overview of the methods used for the development of Quantitative Structure-Property Relationships for physical hazards are presented and discussed regarding the specificities associated to this class of properties. A review of models developed at Ineris is also provided from the first tentative models on the explosivity of nitro compounds to the successful application to the flammability of organic mixtures. Then, a discussion is proposed on the use of QSPR models. Good practices for robust use for QSPR models are recalled with specific comments related to physical hazards, notably for regulatory purpose. Dissemination and training efforts engaged by Ineris are also presented. The potential offered by these predictive methods in terms of in silico design and for the development of new intrinsically safer technologies in safety-by-design strategies is finally discussed. At last, challenges and perspectives to extend the application of chemoinformatics in the field of safety and in particular for the physical hazards of energetic and reactive substances are proposed.

Toward the Mechanistic Understanding of the Additives' Role on Ammonium Nitrate Decomposition: Calcium Carbonate and Calcium Sulfate as Case Studies.

The reaction mechanism involved in the decomposition of ammonium nitrate (AN) in the presence of CaCO3 and CaSO4, commonly used for stabilization and the reduction of explosivity properties of AN, was theoretically investigated using a computational approach based on density functional theory. The presented computational results suggest that both carbonate and sulfate anions can intercept an acid proton from nitric acid issued from the first step of decomposition of AN, thus inhibiting its runaway decomposition and the generation of reactive species (radicals). The reaction then leads to the production of stable products, as experimentally observed. Our modeling outcomes allow for tracing a relationship between the capability of proton acceptance of both carbonate and sulfate anions and the macroscopic behavior of these two additives as inhibitor or inert in the AN mixture.

Impact of the chemical structure on amphiphilic properties of sugar-based surfactants: A literature overview.

In this review, structure-property trends are systematically analyzed for four amphiphilic properties of sugar-based surfactants: critical micelle concentration (CMC), its associated surface tension (γCMC), efficiency (pC20) and Krafft temperature (TK). First, the impact on amphiphilic properties of the alkyl chain size and the presence of branching and/or unsaturation is investigated. Then, various polar head parameters are explored, such as the degree of polymerization of the sugar unit (mono- or oligosaccharides), the chemical nature of the linker and the sugar configuration. Some systematic comparisons between ethoxylated surfactants and sugar-based surfactants are also carried out. While some structural trends with the impact of alkyl chain length or the polar head size are now well understood, this analysis points out that systematic studies of more specific effects of alkyl chain (e.g. branching, unsaturation, presence of rings, position on the polar head) and polar head (e.g. linker, anomeric configuration, internal stereochemistry, cyclic vs. acyclic sugar residues) were scarcer or not available to date. This work encourages the use of these structural trends in the perspective of developing new bio-based surfactants and their consideration in predictive models. It also highlights the need of further experimental tests to fill remaining gaps notably to explore some specific structural features (such as the introduction of rings in the alkyl chain or the position of the alkyl chain on the polar head) and towards applicative properties (like foaming capacity or wettability).

New QSPR Models to Predict the Flammability of Binary Liquid Mixtures.

New Quantitative Structure-Property Relationships (QSPR) are presented to predict the flash point of binary liquid mixtures, based on more than 600 experimental flash points for 60 binary mixtures. Two models are proposed based on a GA-MLR approach that uses a genetic algorithm (GA) variable selection in multilinear regressions (MLR). In these models, mixtures were characterized by a series of mixture descriptors calculated from various mixture formula combining the molecular descriptors of the single compounds constituting the mixtures and their respective molar fractions in the mixture. The best model demonstrated good predictive capabilities with a mean absolute error of only 7.3 °C estimated for an external validation set. Moreover, this model is focused on mixture descriptors applicable to more complex mixtures, i. e. constituted of more than 2 components, and already demonstrated interesting predictions for a series of ternary mixtures.

Investigating the impact of sugar-based surfactants structure on surface tension at critical micelle concentration with structure-property relationships.

HYPOTHESIS: Surface tension of aqueous solutions of surfactants at their critical micelle concentrations (γCMC), may be quantitatively linked to the surfactant structure using Quantitative Structure Property Relationships (QSPR), all other factors held equal (temperature, presence of additive or salts). Thus, QSPR models can allow improved understanding and quantification of structure-γCMC trends, direct γCMC predictions, and finally help to design renewable substitutes for petroleum-based surfactants. EXPERIMENTS AND METHODS: A dataset of 70 γCMC of single surfactants at ambient temperature has been gathered from several research papers. Then, descriptors of the whole structure, of polar heads and of alkyl chains of the 70 surfactants were calculated and introduced in multilinear regressions to evidence the most predictive and physically meaningful structure property relationships. FINDINGS: The best model, based on quantum chemical descriptors, achieved a standard error of 2.4 mN/m on an external validation. Simpler models were also achieved based solely on the count of H atoms of the polar head but with prediction error of 2.9 mN/m. Among all identified factors affecting γCMC of sugar-based surfactants (polar head size, alkyl chain length and branching), polar head size was found to exhibit the only effect clearly taken into account by all the models.

Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides.

Quantitative structure-property relationships represent alternative method to experiments to access the estimation of physico-chemical properties of chemicals for screening purpose at R&D level but also to gather missing data in regulatory context. In particular, such predictions were encouraged by the REACH regulation for the collection of data, provided that they are developed respecting the rigorous principles of validation proposed by OECD. In this context, a series of organic peroxides, unstable chemicals which can easily decompose and may lead to explosion, were investigated to develop simple QSPR models that can be used in a regulatory framework. Only constitutional and topological descriptors were employed to achieve QSPR models predicting the heat of decomposition, which could be used without any time consuming preliminary structure calculations at quantum chemical level. To validate the models, the original experimental dataset was divided into a training and a validation set according to two methods of partitioning, one based on the property value and the other based on the structure of the molecules by the mean of PCA. Four QSPR models were developed upon the type of descriptors and the methods of partitioning. The 2 models issuing from the PCA based method were highlighted as they presented good predictive power and they are easier to apply than our previous quantum chemical based model, since they do not need any preliminary calculations.

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.

Decomposition mechanisms of trinitroalkyl compounds: a theoretical study from aliphatic to aromatic nitro compounds.

The chemical mechanisms involved in the decomposition of trinitroethyl compounds were studied for both aliphatic and aromatic derivatives using density functional theory calculations. At first, in the case of 1,1,1-trinitrobutane, used as a reference molecule, two primary channels were highlighted among the five investigated ones: the breaking of the C-N bond and the HONO elimination. Then, the influence of various structural parameters was studied for these two reactions by changing the length of the carbon chain, adding substituents or double bonds along the carbon chain. If some slight changes in activation energies were observed for most of these features, no modification of the competition between the two investigated reactions was highlighted and the breaking of the C-N bond remained the favoured mechanism. At last, the reactions involving the trinitroalkyl fragments were highlighted to be more competitive than reactions involving nitro groups linked to aromatic cycles in two aromatic systems (4-(1,1,1-trinitrobutyl)-nitrobenzene and 2-(1,1,1-trinitrobutyl)-nitrobenzene). This showed that aromatic nitro compounds with trinitroalkyl derivatives decompose from their alkyl part and may be considered more likely as aliphatic than as aromatic regarding the initiation of their decomposition process.

The ammonium nitrate and its mechanism of decomposition in the gas phase: a theoretical study and a DFT benchmark.

The decomposition mechanism of ammonium nitrate in the gas phase was investigated and fully characterized by means of CBS-QB3 calculations. Five reaction channels were identified, leading to the formation of products (N2, H2O, O2, OH, HNO, NO3) found in the experimental works. The identified mechanism well underlines the origin of the chemical hazard of ammonium nitrate which is related to the exothermicity of the lowest decomposition channels. Furthermore, the high barrier to overcome in the rate determining step well explained the fact that the reaction is not usually spontaneous and requires a significant external stimulus for its onset. An accurate DFT benchmark study was then conducted to determine the most suitable exchange-correlation functional to accurately describe the reaction profile both in terms of structures and thermochemistry. This evaluation supports the use of the M06-2X functional as the best option for the study of ammonium nitrate decomposition and related reactions. Indeed, this level of theory provided the lowest deviations with respect to CBS-QB3 reference values, outperforming functionals especially developed for reaction kinetics.

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.

Oxidation mechanism of aliphatic ethers: theoretical insights on the main reaction channels.

This paper presents a quantum chemical study on oxidation process of a series of aliphatic ethers. On the basis of a detailed theoretical work on diethyl ether oxidation, the mechanism has been reduced at three competing reactions: the ß-scission of the alkyl radical (R(I)OR(II)(•)) issued from the initiation step, the isomerization of the peroxy radical (R(I)OR(II)OO(•)) produced by reaction of the alkyl radical with molecular oxygen, and the hydroperoxide production, a bimolecular reaction between the peroxy radical and an ether molecule that also regenerates a R(I)OR(II)(•) radical. Results obtained from DFT calculations, including thermochemistry and rate constant evaluations, have been reported and discussed. The influence of the presence of the oxygen atom in the ether skeleton has been evaluated by making a comparison between some ethers and parent hydrocarbons. In particular, it has been found that oxygen increases the reactivity of vicinal sites by lowering activation barriers and favors the stabilization of radicals. Direct proportionality relationships have been searched between activation and reaction enthalpies of each class of competing reactions, but one has been found only for the isomerization reaction.

Oxidation mechanism of diethyl ether: a complex process for a simple molecule.

A large number of organic compounds, such as ethers, spontaneously form unstable peroxides through a self-propagating process of autoxidation (peroxidation). Although the hazards of organic peroxides are well known, the oxidation mechanisms of peroxidizable compounds like ethers reported in the literature are vague and often based on old experiments, carried out in very different conditions (e.g. atmospheric, combustion). With the aim to (partially) fill the lack of information, in this paper we present an extensive Density Functional Theory (DFT) study of autoxidation reaction of diethyl ether (DEE), a chemical that is largely used as solvent in laboratories, and which is considered to be responsible for various accidents. The aim of the work is to investigate the most probable reaction paths involved in the autoxidation process and to identify all potential hazardous intermediates, such as peroxides. Beyond the determination of a complex oxidation mechanism for such a simple molecule, our results suggest that the two main reaction channels open in solution are the direct decomposition (ß-scission) of DEE radical issued of the initiation step and the isomerization of the peroxy radical formed upon oxygen attack (DEEOO˙). A simple kinetic evaluation of these two competing reaction channels hints that radical isomerization may play an unexpectedly important role in the global DEE oxidation process. Finally industrial hazards could be related to the hydroperoxide formation and accumulation during the chain propagation step. The resulting information may contribute to the understanding of the accidental risks associated with the use of diethyl ether.

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 (R (2) = 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.

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.

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 (R(2) > 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.

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 dye's family, an advantage over previously designed QSPR schemes. On top of that, the obtained accuracy is comparable to the one of the today's 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.

A theoretical study of the decomposition mechanisms in substituted o-nitrotoluenes.

The pathways corresponding to the most energetically favorable decomposition reactions that can be envisaged for o-nitrotoluene (and 20 of its derivatives) have been studied, using density functional theory, in order to evaluate the influence of substituents' nature (nitro, methyl, amino, carboxylic acid, and hydroxyl) and position. The first mechanism consists of the direct dissociation (homolysis) of the carbon nitrogen bond (CH(3)C(6)H(4)NO(2) = CH(3)C(6)H(4) + NO(2)) whereas the second one is a more complex process initiated by C-H alpha attack and leading to the formation of anthranil and water (C(6)H(4)C(H)ON + H(2)O). For each compound, the initial step of this last channel is the rate limiting one, the Gibbs activation energy of all systems being very close, that is all in the 40-44 kcal/mol range. More important variations have been observed for the C-NO(2) homolysis Gibbs activation energies (46-60 kcal/mol). These variations have been related to electron donor-acceptor properties of substituents by considering significant correlations (R(2) > 0.9) with the Hammett parameters (sigma). Nevertheless, though the influence of substituents on the direct breaking of the C-NO(2) bond was important, the C-H alpha attack remained finally the major decomposition channel for the studied compounds. Our study underlines the complexity of the decomposition process in nitroaromatic compounds and casts some doubts on the characterization of the energetic properties of such molecules only on the basis of C-NO(2) homolysis.

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.