LAPSE:2023.36039
Published Article

LAPSE:2023.36039
Multi-Criteria Screening of Organic Ethanolamines for Efficient CO2 Capture Based on Group Contribution Method
June 7, 2023
Abstract
Amine solvent has attracted much attention due to its high CO2 capture level and wide application range, but its high energy consumption for recycling restricts its large-scale commercialization. In this work, a multi-objective optimization technology based on the group contribution method was used to select potential amine solvents for CO2 capture. This computer-aided molecular design method considers the thermodynamic and kinetic properties of the candidate solvent and evaluates the influence of relevant parameters on solvent performance. Compared with previous experimental methods used to optimize solvent, this method selects potential solvents from a large number of solvent databases based on group contribution. Firstly, a corresponding classification database was established for various kinds of amine solvents. Then, the traditional experiments were used to verify and screen solvents. At the same time, the method was applied to 31 amine absorbents concerning solubility, molar volume, surface tension, heat capacity, viscosity, pKa, saturated vapor pressure, and so on, and seven solvents were found to have comparable performance to MEA, with higher absorption rates and solubility. This method provides guidance for screening CO2 capture absorbents with economic viability, high efficiency, fast absorption rates, and low regeneration energy consumption.
Amine solvent has attracted much attention due to its high CO2 capture level and wide application range, but its high energy consumption for recycling restricts its large-scale commercialization. In this work, a multi-objective optimization technology based on the group contribution method was used to select potential amine solvents for CO2 capture. This computer-aided molecular design method considers the thermodynamic and kinetic properties of the candidate solvent and evaluates the influence of relevant parameters on solvent performance. Compared with previous experimental methods used to optimize solvent, this method selects potential solvents from a large number of solvent databases based on group contribution. Firstly, a corresponding classification database was established for various kinds of amine solvents. Then, the traditional experiments were used to verify and screen solvents. At the same time, the method was applied to 31 amine absorbents concerning solubility, molar volume, surface tension, heat capacity, viscosity, pKa, saturated vapor pressure, and so on, and seven solvents were found to have comparable performance to MEA, with higher absorption rates and solubility. This method provides guidance for screening CO2 capture absorbents with economic viability, high efficiency, fast absorption rates, and low regeneration energy consumption.
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Keywords
amine, Carbon Dioxide Capture, group contribution, multi-criteria screening
Subject
Suggested Citation
Liu B, Yu Y, Liu H, Cui Z, Tian W. Multi-Criteria Screening of Organic Ethanolamines for Efficient CO2 Capture Based on Group Contribution Method. (2023). LAPSE:2023.36039
Author Affiliations
Liu B: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Yu Y: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Liu H: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Cui Z: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Tian W: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China [ORCID]
Yu Y: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Liu H: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Cui Z: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China
Tian W: College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao 266042, China [ORCID]
Journal Name
Processes
Volume
11
Issue
5
First Page
1524
Year
2023
Publication Date
2023-05-16
ISSN
2227-9717
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Original Submission
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PII: pr11051524, Publication Type: Journal Article
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LAPSE:2023.36039
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https://doi.org/10.3390/pr11051524
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[v1] (Original Submission)
Jun 7, 2023
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Jun 7, 2023
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Calvin Tsay
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