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离子液体是熔点相对较低的离子对，预测高能离子液体材料的爆轰特性非常重要，是否可以只用结构描述符即可对爆轰特性作出预测此前尚无研究。来自韩国延世大学的一个研究小组采用量化的结构-性能关系建模法，就离子组成对高能离子液体热性能的影响，建立了预测模型，将回归与遗传算法结合以优化确定描述符的最佳子集。他们研究证实，仅需考虑结构相关的描述符，就能预测离子液体的爆轰性质（爆速、压力和熔化温度），预测精度高于其他预测方法。研究发现，带电原子（C+、N+、C-、N-和O-）与所使用的数十种描述符相比，对性质影响最大，而阳离子/阴离子的组合方式似乎对爆速和压力有重要影响。该模型可为离子组成对高能离子液体热性能的影响做出定量分析，也可为新型高能离子液体的设计提供依据。
该文近期发表于npj Computational Materials 4: 26 (2018); doi:10.1038/s41524-018-0082-y。英文标题与摘要如下，点击阅读原文可以自由获取论文PDF。
Effect of ionic composition on thermal properties of energetic ionic liquids 
Chihyun Park, Minsu Han, Jinbo Kim, Woojae Lee & Eunkyoung Kim
Chemical engineering; Organic chemistry
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 R2 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.
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