Prediction of the thermal decomposition temperatures of imidazolium ILs based on norm indexes

Thermal decomposition temperature (T_d) is a vital feature to assess the thermal hazard of ionic liquids (ILs). In this approach, a statistically significant quantitative structure-property relationship (QSPR) model was developed to forecast the T_d of imidazolium ILs merely derived from their molecular structures. The new proposed norm indexes were employed to characterize not only the structural characteristics of anions and cations but also the interaction between anions and cations. The genetic algorithm-based multiple linear regression (GA-MLR) method was adopted to choose the best set of norm indexes that oblige a prominent contribution to the T_d of imidazolium ILs. The results prediction model was obtained from a multilinear equation with thirteen variables, as consisting of three cationic descriptors, seven anionic descriptors, and three interaction descriptors. The squared correlation coefficients (R²) and the root-mean-squared error (RMSE) of the resulting model are 0.895 and 21.626, respectively. The developed model was then rigorously verified by various validation methods, and thoroughly extensively compared with formerly circulated published models. The results showed satisfactory sturdiness and accountability of the model, which would be considered to be able to forecast the T_d of imidazolium ILs and provide some guidelines for designing as well manufacturing safer ILs with better thermal stability.