https://doi.org/10.1140/epjp/s13360-022-03261-x
Regular Article
CFD investigation of CO2 separation from anesthesia gaseous stream applying novel cholinium lysinate amino acid-based ionic liquid inside the gas–liquid membrane contactor
1
School of Computer Science and Engineering, Xi’an Technological University, 710021, Xi’an, China
2
Department of Petroleum and Chemical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
3
Institute of Research and Development, Duy Tan University, 550000, Da Nang, Vietnam
4
The Faculty of Environment and Chemical Engineering, Duy Tan University, 550000, Da Nang, Vietnam
b
Taghvaiali@yahoo.com
c
mahdighadiri@duytan.edu.vn
Received:
17
August
2022
Accepted:
2
September
2022
Published online:
14
September
2022
Recently, amino acid-based ionic liquids (AAILs) have been introduced as an encouraging chemical absorbent for the efficient separation of CO2 acidic pollutant from disparate gaseous flows. These absorbents have shown their excellent potential of utilization in membrane-based gas separation processes thanks to their brilliant advantages such as bioavailability, eco-friendliness and high separation performance. The important goal of this research is to develop a 2D simulation to estimate the separation yield of CO2 from anesthesia gaseous mixture inside the hollow fiber membrane contactor (HFMC). Cholinium lysinate ([Cho+][Lys−]) AAIL has been employed as a novel chemical absorbent. Additionally, a finite element-based mathematical model has been employed to analyze the main transport equations (momentum and mas) inside different domains of HFMC. Based on the results, [Cho+][Lys−] AAIL can be introduced as an efficacious chemical absorbent with the capability of separation about 96% of inlet CO2. By evaluating the effect of each parameter on the CO2 separation efficiency, it can be said that increment of liquid flow rate, porosity, fiber counts and module length can enhance the separation performance, while an increase in the gas flow rate diminishes the separation efficiency of CO2 pollutant from anesthesia gaseous stream.
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