Development of simple QSPR models for the impact sensitivity of nitramines - Ineris - Institut national de l'environnement industriel et des risques Accéder directement au contenu
Article Dans Une Revue Journal of Loss Prevention in the Process Industries Année : 2014

Development of simple QSPR models for the impact sensitivity of nitramines

Résumé

Quantitative structure–property relationships represent a powerful method alternative to experiments to access the estimation of physico-chemical properties of chemical substances. Such predictions are useful for screening purpose at R&D level. Moreover, this approach is encouraged by the REACH regulation for the collection of data when used cleanly and transparently. The impact sensitivities of 60 nitramine compounds were investigated in a QSPR study following the five principles of validation defined by OECD for the use of models in a regulatory framework. Only constitutional descriptors were employed to achieve QSPR models that could be used without any time consuming preliminary structure calculations at quantum chemical level. To validate models, the original data set was partitioned into a training and validation set. A series of 17 partitions, based on two ratios (40/20 and 45/15) and two division methods (property ranking and random division), were used to achieve this goal. From these partitions, four models exhibiting good predictive power using only constitutional descriptors were highlighted. These models are easier to apply than our previous quantum chemical based model, since they do not need any preliminary calculations.
Fichier non déposé

Dates et versions

ineris-01855539 , version 1 (08-08-2018)

Identifiants

Citer

Guillaume Fayet, Patricia Rotureau. Development of simple QSPR models for the impact sensitivity of nitramines. Journal of Loss Prevention in the Process Industries, 2014, 30, pp.1-8. ⟨10.1016/j.jlp.2014.04.005⟩. ⟨ineris-01855539⟩

Collections

INERIS
26 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More