作者：Jie Xu, Ligen Zhu, Dong Fang, Luoxin Wang, Shili Xiao, Li Liu, Weilin Xu
关键字：QSPR, Impact sensitivity
论文来源：期刊
发表时间：2012年
The quantitative structure–property relationship (QSPR) studies were performed between molecular structures and impact sensitivity for a diverse set of nitro energetic compounds based on threedimensional (3D) descriptors. The entire set of 156 compounds was divided into a training set of 127 compounds and a test set of 29 compounds according to Kennard and Stones algorithm. Multiple linear regression (MLR) analysis was employed to select the best subset of descriptors and to build linear models; while nonlinear models were developed by means of artificial neural network (ANN). The obtained models with ten descriptors involved show good predictive power for the test set: a squared correlation coefficient (R2) of 0.7222 and a standard error of estimation (s) of 0.177 were achieved by the MLR model;
while by the ANN model, R2 and s were 0.8658 and 0.130, respectively. Therefore, the proposed models can be used to predict the impact sensitivity of new nitro compounds for engineering.