Literature DB >> 22871414

Development of validated QSPR models for impact sensitivity of nitroaliphatic compounds.

Vinca Prana1, Guillaume Fayet, Patricia Rotureau, Carlo Adamo.   

Abstract

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.
Copyright © 2012 Elsevier B.V. All rights reserved.

Mesh:

Substances:

Year:  2012        PMID: 22871414     DOI: 10.1016/j.jhazmat.2012.07.036

Source DB:  PubMed          Journal:  J Hazard Mater        ISSN: 0304-3894            Impact factor:   10.588


  3 in total

1.  Computational study of the structure and properties of bicyclo[3.1.1]heptane derivatives for new high-energy density compounds with low impact sensitivity.

Authors:  Mingran Du
Journal:  J Mol Model       Date:  2017-12-18       Impact factor: 1.810

2.  Models for predicting impact sensitivity of energetic materials based on the trigger linkage hypothesis and Arrhenius kinetics.

Authors:  Tomas L Jensen; John F Moxnes; Erik Unneberg; Dennis Christensen
Journal:  J Mol Model       Date:  2020-03-04       Impact factor: 1.810

3.  Applying machine learning techniques to predict the properties of energetic materials.

Authors:  Daniel C Elton; Zois Boukouvalas; Mark S Butrico; Mark D Fuge; Peter W Chung
Journal:  Sci Rep       Date:  2018-06-13       Impact factor: 4.379

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.