On the use of descriptors arising from the conceptual density functional theory for the prediction of chemicals explosibility

Electrophilicity index revisited

This review aims to be a comprehensive, authoritative, critical, and accessible review of general interest to the chemistry community; because the electrophilicity index is a very useful global reactivity descriptor defined within a conceptual density functional theory framework. Our group has also introduced electrophilicity based new global and local reactivity descriptors and also new associated electronic structure principles, which are important indicators of structure, stability, bonding, reactivity, interactions, and dynamics in a wide variety of physico-chemical systems and processes. This index along with its local counterpart augmented by the associated electronic structure principles could properly explain molecular vibrations, internal rotations and various types of chemical reactions. The concept of the electrophilicity index has been extended to dynamical processes, excited states, confined environment, spin-dependent and temperature-dependent situations, biological activity, site selectivity, aromaticity, charge removal and acceptance, presence of external perturbation through solvents, external electric and magnetic fields, and so forth. Although electrophilicity and its local variant can adequately interpret the behavior of a wide variety of systems and different physico-chemical processes involving them, their predictive potential remains to be explored. An exhaustive review on all these aspects will set the tone of the future research in that direction.

Exploratory and machine learning analysis of the stability constants of HgII- triazene ligands complexes

Knowing stability constants for the complexes HgII with extracting ligands is very important from environmental and therapeutic standpoints. Since the selectivity of ligands can be stated by the stability constants of cation–ligand complexes, quantitative structure–property relationship (QSPR) investigations on binding constant of HgII complexes were done. Experimental data of the stability constants in ML2 complexation of HgII and synthesized triazene ligands were used to construct and develop QSPR models. Support vector machine (SVM) and multiple linear regression (MLR) have been employed to create the QSPR models. The final model showed squared correlation coefficient of 0.917 and the standard error of calibration (SEC) value of 0.141 log K units. The proposed model presented accurate prediction with the Leave-One-Out cross validation ( Q LOO 2  = 0.756) and validated using Y-randomization and external test set. Statistical results demonstrated that the proposed models had suitable goodness of fit, predictive ability, and robustness. The results revealed the importance of charge effects and topological properties of ligand in HgII - triazene complexation.

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.

Significance of Theoretical Decomposition Enthalpies for Predicting Thermal Hazards

Much effort is currently put into the development of models for predicting decomposition enthalpies measured using differential scanning calorimetry (DSC). As an alternative to the purely empirical schemes reported so far, this work relies on theoretical values obtained on the basis of simple assumptions. For nitroaromatic compounds (NACs) studied in sealed sample cells, our approach proves clearly superior to previous ones. In contrast, it correlates poorly with data measured in pin-hole sample cells. Progress might be obtained through a combination of the present approach with the usual Quantitative Structure-Property Relationships (QSPR) methodologies. This work emphasizes the significance of the theoretical decomposition enthalpy as a fundamental descriptor for the prediction of DSC values. In fact, the theoretical value provides a valuable criterion to characterize thermal hazards, as a complement to experimental decomposition temperatures.

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.

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.