Premium
A New General Correlation for Predicting Impact Sensitivity of Energetic Compounds
Author(s) -
Keshavarz Mohammad H.
Publication year - 2013
Publication title -
propellants, explosives, pyrotechnics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.56
H-Index - 65
eISSN - 1521-4087
pISSN - 0721-3115
DOI - 10.1002/prep.201200128
Subject(s) - explosive material , sensitivity (control systems) , artificial neural network , biological system , correlation , chemistry , least squares function approximation , molecular descriptor , mathematics , quantitative structure–activity relationship , computational chemistry , statistics , computer science , engineering , stereochemistry , organic chemistry , machine learning , biology , geometry , electronic engineering , estimator
This paper describes an improved simple model for prediction of impact sensitivity of different classes of energetic compounds containing nitropyridines, nitroimidazoles, nitropyrazoles, nitrofurazanes, nitrotriazoles, nitropyrimidines, polynitroarenes, benzofuroxans, polynitroarenes with α‐CH, nitramines, nitroaliphatics, nitroaliphatic containing other functional groups, and nitrate energetic compounds. The model is based on some molecular structural parameters. It is applied for 90 explosives, which have different molecular structures. The predicted results are compared with outputs of complex neural network approach as one of the best available methods. Root mean squares (rms) of deviations of different energetic compounds are 24 and 49 cm, corresponding to 5.88 and 12.01 J with 2.5 kg dropping mass, for new and neural network methods, respectively. The novel model also predicts good results for eight new synthesized and miscellaneous explosives with respect to experimental data.