离子液体
萃取(化学)
数量结构-活动关系
化学
吡啶
噻吩
COSMO-RS公司
选择性
萃取蒸馏
C4毫米
非随机双液模型
环丁砜
溶剂
烟气脱硫
稀释
活度系数
色谱法
有机化学
热力学
催化作用
水溶液
物理
立体化学
作者
Daili Peng,Anne-Jan Kleiweg,J.G.M. Winkelman,Zhen Song,Francesco Picchioni
标识
DOI:10.1021/acssuschemeng.0c07866
摘要
A hierarchical hybrid method combining experimental-database-derived estimation of extraction performance, quantitative structure–property relationship (QSPR)-based assessment of IL physical and environmental properties, liquid–liquid extraction (LLE) measurement, and process evaluation is proposed to screen practically suitable ionic liquid (IL) solvents for different extractions. From the literature, 47 424 infinite dilution activity coefficient (IDAC) data including 12 IL families (e.g., imidazolium, pyridinium, ammonium, etc.) and 13 organic families (e.g., alkanes, aromatics, alcohols, etc.) are collected. On the basis of the IDAC data, the extraction performance of ILs for a specific separation can be estimated in terms of the distribution ratio and selectivity at infinite dilution. The ILs with potentially high extraction performance and meeting the physical and environmental properties criteria are selected to perform LLE experiments. Subsequently, process simulation and evaluation using the selected IL solvents are performed by Aspen Plus. To exemplify the proposed method, the extractive desulfurization (EDS) process is taken as a case study, where [EMIM][MESO3] (1-ethyl-3-methylimidazolium methanesulfonate) and [EIM][NO3] (1-ethylimidazolium nitrate) are selected after IDAC database searching and QSPR analysis. Experimental LLE with the two ILs are determined, demonstrating their promising extraction performance with the maximum selectivity (S23max) for thiophene/heptane of 420 and 281.9, respectively. By fitting the NRTL model correspondingly, two processes using the screened ILs and sulfolane are developed and compared using Aspen Plus. It turns out that the two ILs save 66% and 48% in solvent requirements and 54% and 55% in energy consumption compared to those of sulfolane for the EDS task, respectively.
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