关于离子液体和 C6-烃类互溶性的 COSMO-RS 系统研究

IF 9.1 Q1 ENGINEERING, CHEMICAL Green Chemical Engineering Pub Date : 2022-12-02 DOI:10.1016/j.gce.2022.11.002
Chuxin Qi, Zhen Song, Hongye Cheng, Lifang Chen, Zhiwen Qi
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引用次数: 0

摘要

在考虑使用离子液体(ILs)进行涉及非极性或弱极性碳氢化合物的反应和分离时,了解离子液体与碳氢化合物的互溶性行为至关重要。本文以苯、环己烯、环己烷和正己烷这四种典型的 C6 碳氢化合物为代表,基于 COSMO-RS 模型系统地研究了 ILs 与非极性或弱极性碳氢化合物的互溶性。首先,通过比较相关体系在无限稀释和二元/三元液液平衡条件下的实验和预测烃在惰性气体中的活性系数,评估了 COSMO-RS 在这些体系中的可靠性。然后,预测了四种碳氢化合物和 13,650 个 IL(由 210 个阳离子和 65 个阴离子组成)的相互溶解度。通过分析相互作用能和筛网电荷分布,进一步分析了不同IL结构特征(包括烷基链长、阳离子族/对称性/官能团和阴离子)对IL-烃互溶性行为的影响。互溶性数据库及其确定的结构效应可为相关应用中的IL选择提供有用的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A systematic COSMO-RS study on mutual solubility of ionic liquids and C6-hydrocarbons

When considering the usage of ionic liquids (ILs) for reactions and separations involving non-polar or weak-polar hydrocarbons, the knowledge of the mutual solubility behaviors of ILs and hydrocarbons is of the utmost importance. In this work, taking four typical C6-hydrocarbons namely benzene, cyclohexene, cyclohexane, and hexane as representatives, the mutual solubility of ILs and non-polar or weak-polar hydrocarbons are systematically studied based on the COSMO-RS model. The reliability of COSMO-RS for these systems is first evaluated by comparing experimental and predicted hydrocarbon-in-IL activity coefficient at infinite dilution and binary/ternary liquid-liquid equilibria of related systems. Then, the mutual solubility of the four hydrocarbons and 13,650 ILs (composed by 210 cations and 65 anions) are predicted. The effect of different IL structural characteristics including alkyl chain length, cation family/symmetry/functional group, and anion on the IL-hydrocarbon mutual solubility behaviors are further analyzed by the analyses of interaction energy and screen charge distribution. The mutual solubility databases and the structural effects identified thereon could provide useful guidance for IL selection in related applications.

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来源期刊
Green Chemical Engineering
Green Chemical Engineering Process Chemistry and Technology, Catalysis, Filtration and Separation
CiteScore
11.60
自引率
0.00%
发文量
58
审稿时长
51 days
期刊最新文献
OFC: Outside Front Cover Outside Back Cover Outside Back Cover OFC: Outside Front Cover Integration of physical information and reaction mechanism data for surrogate prediction model and multi-objective optimization of glycolic acid production
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