Machine Learning-Boosted Design of Ionic Liquids for CO2 Absorption and Experimental Verification,The Journal of Physical Chemistry B

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Machine Learning-Boosted Design of Ionic Liquids for CO2 Absorption and Experimental Verification
The Journal of Physical Chemistry B ( IF 2.8 ) Pub Date : 2023-02-24 , DOI: 10.1021/acs.jpcb.2c07305
Nahoko Kuroki _{1,

2} , Yuki Suzuki ₃ , Daisuke Kodama ₃ , Firoz Alam Chowdhury ₄ , Hidetaka Yamada _{4,

5} , Hirotoshi Mori ₁

Affiliation

Efficient CO₂ capture is indispensable for achieving a carbon-neutral society while maintaining a high quality of life. Since the discovery that ionic liquids (ILs; room-temperature molten salts) can absorb CO₂, various solvents composed of molecular ions have been studied. However, it is challenging to observe the properties of each isolated ion component to control the function of ILs as they are mixtures of ions. Finding the optimal cation–anion combination for the CO₂ absorbent from their enormous chemical space had been impossible in a practical sense. This study applied electronic structure informatics to explore ILs with high CO₂ solubility from 402,114 IL candidates. The feature variables were determined by a set of cheap quantum chemistry calculations for isolated small-ion fragments, and the importance of molecular geometries and electronic states governing molecular interactions was identified via the wrapper method. As a result, it was clearly shown that the electronic states of ionic species must have essential roles in the CO₂ physisorption capacity of ILs. Considering synthetic easiness for the candidates narrowed by the machine learning model, trihexyl(tetradecyl)phosphonium perfluorooctanesulfonate was synthesized. Using a magnetic suspension balance, it was experimentally confirmed that this IL has higher CO₂ solubility than trihexyl(tetradecyl)phosphonium bis(trifluoromethanesulfonyl)amide, which is the previous best IL for CO₂ absorption.

中文翻译：

用于 CO2 吸收和实验验证的离子液体的机器学习增强设计

高效的 CO ₂捕集对于实现碳中和社会，同时保持高质量的生活是不可或缺的。自从发现离子液体（ILs；室温熔盐）可以吸收 CO ₂以来，已经研究了由分子离子组成的各种溶剂。然而，观察每个孤立离子成分的特性以控制 IL 的功能具有挑战性，因为它们是离子的混合物。从实际意义上来说，从巨大的化学空间中寻找 CO ₂吸收剂的最佳阳离子-阴离子组合是不可能的。本研究应用电子结构信息学探索具有高CO _{2的离子液体}来自 402,114 名 IL 候选者的溶解度。特征变量由一组针对孤立的小离子碎片的廉价量子化学计算确定，分子几何形状和电子态控制分子相互作用的重要性通过包装方法确定。结果，清楚地表明离子物质的电子态必须在离子液体的 CO ₂物理吸附能力中发挥重要作用。考虑到机器学习模型缩小的候选化合物的合成容易性，合成了三己基（十四烷基）磷鎓全氟辛烷磺酸盐。使用磁悬浮天平，通过实验证实，该离子液体具有更高的 CO ₂溶解度高于三己基（十四烷基）磷双（三氟甲磺酰基）酰胺，后者是以前对 CO ₂吸收最好的 IL。

更新日期：2023-02-24

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