QSAR correlation of the melting points for imidazolium bromides and imidazolium chlorides ionic liquids

Abstract

The melting points of ionic liquids (ILs) of imidazolium bromides and imidazolium chlorides have been investigated by means of quantitative structure–activity relationship (QSAR) approach in order to develop prediction models for predicting the melting points of ionic liquid salts. The cationic structures of these ILs were optimized by means of Hyperchem software and MOPAC program. QSAR module of Materials Studio software and Genetic Algorithm (GA) programs were employed to calculate and select the structure descriptors of ILs, then prediction models correlating the selected structure descriptors and melting points of ionic liquids were set up by using the multiple linear regressions (MLR) method and the back-propagation artificial neural network (BP ANN) method, separately. Finally, the obtained QSAR models, including MLR model and BP ANN model, were validated by external test sets. In this work, three data sets, which were 30 imidazolium bromides, 20 imidazolium chlorides and the merging of above two data sets, respectively, were used to investigate the QSAR correlation of the melting points of ILs. The results demonstrated that the prediction mean absolute errors (MAEs) of MLR models for test sets of those three data sets were in the order of 20.52 K, 13.59 K and 21.95 K, and the prediction MAEs of BP ANN models were 8.77 K, 4.98 K and 9.31 K, respectively. It indicated that the predictions of two models for all melting points of ILs were reliable, and the prediction precision of BP ANN model was higher than that of MLR model.