QSPR studies of impact sensitivity of nitro energetic compounds using three-dimensional descriptors
作者：Jie Xu, Ligen Zhu, Dong Fang, Luoxin Wang, Shili Xiao, Li Liu, Weilin Xu
關(guān)鍵字：QSPR, Impact sensitivity
論文來源：期刊
發(fā)表時間：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.