Ionic liquids: Prediction of melting point by molecular-based model

Abstract

The aim of is this study is to develop molecular-based model for prediction of melting points of diverse classes of ionic liquids. For this purpose, exhaustive literature survey was conducted in order to collect comprehensive database of the melting points of ionic liquids. The melting points of 808 diverse ionic liquids belongs to Sulfonium, Ammonium, Pyridinium, 1,3-Dialkyl imidazolium, Tri-alkyl imidazolium, Phosphonium, Pyrrolidinium, Double imidazolium, 1-Alkyl imidazolium, Piperidinium, Pyrroline, Oxazolidinium, Amino acids, Guanidinium, Morpholinium, Isoquinolinium and Tetra-alkyl imidazolium have been collected from 131 various references. Quantitative Structure–Property Relationship (QSPR) approach was applied in order to develop a reliable model for the prediction of the melting points of ionic liquids. As far as the authors concern, the investigated data has the broadest range of anion and cation structures among the previous studies which enhances its generality to predict melting point of unknown ionic liquids. The final QSPR model derived by Genetic Function Approximation (GFA) contains 12 descriptors and quantified by the following statistical parameters: R2train=0.658, R2test=0.721 and Average Absolute Relative Deviation (AARD)=7.3%. The Applicability Domain (AD) of the model is also investigated. It turns out that the model's domain is defined broadly enough to contain all the trained and test sets which verified the reliability of the model. Finally, the proposed model has been scrutinized by several validation techniques and its robustness and reliability is investigated. The results of the validation techniques indicate the present model is robust, stable and reliable one.