Toward a Materials Genome Approach for Ionic Liquids: Synthesis Guided by Ab Initio Property Maps

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• 作者：Fangyong Yan ; Michael Lartey ; Kuldeep Jariwala ; Sage Bowser ; Krishnan Damodaran ; Erik Albenze ; David R. Luebke ; Hunaid B. Nulwala ; Berend Smit ; Maciej Haranczyk
• 刊名：Journal of Physical Chemistry B
• 出版年：2014
• 出版时间：November 26, 2014
• 年：2014
• 卷：118
• 期：47
• 页码：13609-13620
• 全文大小：656K
• ISSN：1520-5207

文摘

The Materials Genome Approach (MGA) aims to accelerate development of new materials by incorporating computational and data-driven approaches to reduce the cost of identification of optimal structures for a given application. Here, we use the MGA to guide the synthesis of triazolium-based ionic liquids (ILs). Our approach involves an IL property-mapping tool, which merges combinatorial structure enumeration, descriptor-based structure representation and sampling, and property prediction using molecular simulations. The simulated properties such as density, diffusivity, and gas solubility obtained for a selected set of representative ILs were used to build neural network models and map properties for all enumerated species. Herein, a family of ILs based on ca. 200鈥?00 triazolium-based cations paired with the bis(trifluoromethanesulfonyl)amide anion was investigated using our MGA. Fourteen representative ILs spreading the entire range of predicted properties were subsequently synthesized and then characterized confirming the predicted density, diffusivity, and CO₂ Henry鈥檚 Law coefficient. Moreover, the property (CO₂, CH₄, and N₂ solubility) trends associated with exchange of the bis(trifluoromethanesulfonyl)amide anion with one of 32 other anions were explored and quantified.