文献类型：期刊文献

英文题名：COSMO-descriptor based computer-aided ionic liquid design for separation processes Part II: Task-specific design for extraction processes

作者：Zhang, Jianan[1];Qin, Lei[1];Peng, Daili[1];Zhou, Teng[2];Cheng, Hongye[1];Chen, Lifang[1];Qi, Zhiwen[1]

机构：[1]East China Univ Sci & Technol, Sch Chem Engn, Max Planck Partner Grp, State Key Lab Chem Engn, Shanghai 200237, Peoples R China;[2]Max Planck Inst Dynam Complex Tech Syst, Sandtorstr 1, D-39106 Magdeburg, Germany

年份：2017

卷号：162

起止页码：364

外文期刊名：CHEMICAL ENGINEERING SCIENCE

收录：;EI(收录号：20170203235048);WOS:【SCI-EXPANDED(收录号:WOS:000397832600031)】；

基金：This research is supported by the National Natural Science Foundation of China (NSFC U1462123, 21576081), Major State Basic Research Development Program of China (973 Program 2012CB720502), PetroChina Innovation Foundation, Fundamental Research Funds for the Central Universities of China, and 111 Project (B08021).

语种：英文

外文关键词：Ionic liquids; Computer-aided molecular design; Simulated annealing; Genetic algorithm; Extractive separation

摘要：A computer-aided ionic liquid design (CAILD) framework is presented to identify optimal structures of ionic liquids (ILs) for specific separation processes. The design task is formulated as an optimization problem with the objective of maximizing the IL separation performance. In order to result in ILs with high practical application potential, constraints on their physicochemical properties are considered in CAILD. IL candidates are represented by rooted trees, which facilitate the prediction of their a-profiles and cavity volumes from the COSMO-GC-IL method proposed in the first part of this work. A mixed simulated annealing-genetic algorithm (MSAGA) algorithm is developed and used for solving the optimization-based CAILD problem. The proposed CAILD framework is tested to design ILs for two extraction processes, i.e., separation of benzene-cyclohexane and heptane-thiophene. The result demonstrates that MSAGA can reliably and efficiently solve the problem and the finally identified ILs show improved separation performance than literature-reported ones. (C) 2016 Elsevier Ltd. All rights reserved.