A Quantitative Structure - Property Relationship (QSPR) study was carried out to model the melting points for a diverse set of 288 potential Ionic Liquids (ILs) including pyridinium bromides, imidazolium bromides, benzimidazolium bromides, and 1-substituted 4-amino-1,2,4-triazolium bromides. Based on the calculated descriptors by CODESSA program, a Principal Component Analysis (PCA) was performed on the whole data to detect the homogeneities in the dataset and to assist the separation of the data into representative training and test sets. Heuristic Method (HM) and Projection Pursuit Regression (PPR) were used to develop linear and nonlinear models between the descriptors and the melting points. The PPR model gave a high predictive correlation coefficient (R 2) of 0.810 and an Average of Absolute Relative Deviation (AARD) of 17.75%, which are better than those by HM model (R2=0.712, AARD=24.33%) indicating that PPR is better for the prediction of the melting points. In addition, the descriptors selected by HM can give some insight into factors that can affect the melting points, i.e., benzene ring structure, rotatable bonds, branching, symmetry, and intramolecular electronic effects. This information would be very useful in the design of the potential ILs with desired melting points.
- Ionic liquids
- Melting points
- Projection pursuit regression
- Quantitative structure - property relationship