Predicting thermal decomposition temperatures of imidazolium-based energetic ionic liquids using norm indexes

Energetic ionic liquids (EILs) have been widely applied in propellants, high-energy explosives, etc., but may trigger thermal hazards. Predicting the thermal decomposition temperature (T_d) is of great importance to EILs. In this work, a quantitative structure–property relationship model is developed to predict the T_d of imidazolium-based EILs from their molecular structures. By using the norm index descriptors, both the structure of ions and the interaction of anions with cations are well described. To screen out the optimal subset of norm indexes that are closely related to T_d of imidazolium-based EILs, the genetic algorithm-based multiple linear regression method is used. The developed model demonstrates the high accuracy, reaching a coefficient of determination (R²), leave-one-out cross-validation coefficient QLoo2, and external validation coefficient QEXT2 as 0.842, 0.842, and 0.833 between the predicted against experimental values, respectively. It is extensively validated by internal and external validation strategies. Compared with the reported models, our proposed model based on norm indexes demonstrates a stronger predictive ability. This work provides a reliable model to predict the T_d of imidazolium-based EILs, which is expected to provide guidance for the design of new EILs.