标题:Novel Postcombustion Capture Process for CO2 from the Flue Gas of Coal-Fired Power Plants Using a Green Deep Eutectic Solvent
作者:Wang, Yinglong; Liu, Yigang; Liu, Xiaobin; Li, Guoxuan; Qi, Jianguang; Yang, Jingwei; Zhu, Zhaoyou; Ma, Yixin; Gao, Jun; Meng, Fanqi 更多
作者机构:[Wang, Yinglong; Liu, Yigang; Liu, Xiaobin; Li, Guoxuan; Qi, Jianguang; Yang, Jingwei; Zhu, Zhaoyou; Meng, Fanqing] Qingdao Univ Sci & Technol, Coll C 更多
通讯作者:Meng, Fanqing;Meng, FQ
通讯作者地址:[Meng, FQ]Qingdao Univ Sci & Technol, Coll Chem Engn, Qingdao 266042, Peoples R China.
来源:ACS SUSTAINABLE CHEMISTRY & ENGINEERING
出版年:2020
卷:8
期:5
页码:2236-2245
DOI:10.1021/acssuschemeng.9b06026
关键词:postcombustion; deep eutectic solvent; process simulation; sensitivity; analysis; exergy analysis
摘要:Green, efficient, and low energy consumption capture of CO2 from the flue gas of coal-fired power plants has been one of the most popular research topics in the world. In this work, a concept process of postcombustion capture (PCC) using a choline chloride/urea (1:2) deep eutectic solvent (DES) as a physical solvent was proposed. The DES-based PCC process is modeled and simulated using commercial Aspen Plus simulation software. The required parameters were studied and further embedded in Aspen Plus. The simulation results show that the process has a good capture effect; the capture ratio of CO2 is 97.33%, and the purity of CO2 in the product gas is 99.42%. Through sensitivity analysis, the influence of several key parameters on the process performance is studied and reasonable operating conditions are determined. Exergy analysis is carried out for a CO2 absorption unit and a solvent regeneration unit. The results show that the total exergy efficiency of these two units is 74.28%. The new DES-based PCC process has great potential and will provide a new way to capture CO, in the flue gas of coal-fired power plants.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079826023&doi=10.1021%2facssuschemeng.9b06026&partnerID=40&md5=a038a134a940d2c63dd7a1a81d658fb8
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