Prediction of refractive indices of ionic liquids - A quantitative structure-property relationship based model

In this communication, a reliable Quantitative Structure−Property Relationship (QSPR) model is developed to predict the refractive indices, nD, of ionic liquids at different temperatures. A dataset comprising 931 experimental data values of refractive index (λ = 589 nm) for 97 ionic liquids (extracted from the NIST Standard Reference Database) was used to develop and evaluate the model (80% of the data used as a training set and 20% as a test set). In this study, the effects of both anions and cations are considered in the development of the model. Genetic function approximation (GFA) is applied to select the model parameters (molecular descriptors) and develop a linear QSPR model. Statistical analysis of the performance of the model with respect to the dataset indicates an average absolute relative deviation (AARD%) of 0.51, a coefficient of determination (R2) of 0.935, and a root mean square of error (RMSE) of 1.07 × 10−2.