A model to predict the effect of ionic composition on the thermal properties of energetic ionic liquids was developed by quantitative structure-property relationship modeling, which predicted the detonation velocity, pressure, and melting temperature of energetic ionic liquids. A hybrid approach was used to determine the optimal subset of descriptors by combining regression with the genetic algorithm as an optimization method. The model showed the high accuracy, reaching a correlation factor of R 2 as 0.71, 0.73 and 0.68 for the correlation between the calculated detonation velocity, pressure and melting temperature against reported values. It was validated extensively and compared to the Kamlet-Jacobs equation. The effect of ion composition on the thermal properties of energetic ionic liquids could be quantitatively analyzed through the developed model, to give an insight for the design of new energetic ionic liquids.
All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Materials Science(all)
- Mechanics of Materials
- Computer Science Applications