First QSPR models to predict the thermal stability of potential self-reactive substances
- Self-reactive substances are unstable chemical substances which can easily decompose and may lead to explosion in transport, storage, or process situations. For this reason, their thermal stability properties are required to assess possible process safety issues and for classification purpose. In this study, the first quantitative structure–property relationships (QSPR) dedicated to this class of compounds were developed to predict the heat of decomposition of possible self-reactive substances from their molecular structures. The database used to develop and validate the models was issued from a dedicated experimental campaign on 50 samples using differential scanning calorimetry in homogeneous experimental conditions. QSPR models were derived using the GA-MLR methods (using a genetic algorithm and multi-linear regressions) using molecular descriptors calculated by Dragon software based on two types of inputs: 3D molecular structures determined using the density functional theorySelf-reactive substances are unstable chemical substances which can easily decompose and may lead to explosion in transport, storage, or process situations. For this reason, their thermal stability properties are required to assess possible process safety issues and for classification purpose. In this study, the first quantitative structure–property relationships (QSPR) dedicated to this class of compounds were developed to predict the heat of decomposition of possible self-reactive substances from their molecular structures. The database used to develop and validate the models was issued from a dedicated experimental campaign on 50 samples using differential scanning calorimetry in homogeneous experimental conditions. QSPR models were derived using the GA-MLR methods (using a genetic algorithm and multi-linear regressions) using molecular descriptors calculated by Dragon software based on two types of inputs: 3D molecular structures determined using the density functional theory (DFT), allowing access to three-dimensional descriptors, and from SMILES codes, favoring the access to simpler models, requiring no preliminary quantum chemical calculations. All models respected the OECD validation guidelines for regulatory ac ceptability of QSPR models. They were tested by internal and external validation tests and their applicability domains were defined and analyzed.…
Autor*innen: | F. Guillaume, Annett Knorr, P. Rotureau |
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Dokumenttyp: | Zeitschriftenartikel |
Veröffentlichungsform: | Verlagsliteratur |
Sprache: | Englisch |
Titel des übergeordneten Werkes (Englisch): | Process Safety and Environmental Protection (Elsevier) |
Jahr der Erstveröffentlichung: | 2022 |
Organisationseinheit der BAM: | 2 Prozess- und Anlagensicherheit |
2 Prozess- und Anlagensicherheit / 2.3 Einstufung von Gefahrstoffen und -gütern | |
Verlag: | Elsevier Ltd. |
Jahrgang/Band: | 163 |
Erste Seite: | 191 |
Letzte Seite: | 199 |
DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten |
Freie Schlagwörter: | Genetic algorithm; Quantitative Structure-Property Relationships; Self-reactive substances; Thermal stability |
Themenfelder/Aktivitätsfelder der BAM: | Material |
DOI: | 10.1016/j.psep.2022.05.017 |
ISSN: | 0957-5820 |
Verfügbarkeit des Dokuments: | Datei im Netzwerk der BAM verfügbar ("Closed Access") |
Datum der Freischaltung: | 08.09.2022 |
Referierte Publikation: | Ja |
Datum der Eintragung als referierte Publikation: | 08.09.2022 |