A predictive group-contribution framework for the thermodynamic modelling of CO
absorption in cyclic amines, alkyl polyamines, alkanolamines and phase-change amines: New data and SAFT-
Mie parameters
absorption in cyclic amines, alkyl polyamines, alkanolamines and phase-change amines: New data and SAFT-
Mie parameters
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Published version
Author(s)
Type
Journal Article
Abstract
A significant effort is under way to identify improved solvents for carbon dioxide (CO
) capture by chemisorption. We develop a predictive framework that is applicable to aqueous solvent + CO
mixtures containing cyclic amines, alkyl polyamines, and alkanolamines. A number of the mixtures studied exhibit liquid–liquid phase separation, a behaviour that has shown promise in reducing the energetic cost of CO
capture. The proposed framework is based on the SAFT-
Mie group-contribution (GC) approach, in which chemical reactions are described via physical association models that allow a simpler, implicit, treatment of the chemical speciation characteristic of these mixtures. We use previously optimized group interaction parameters between some amine groups and water (Perdomo et al., 2021), and develop new group interactions for the cNH, cN, NH2, NH, N, cCHNH, and cCHN groups with CO2; a set of second-order group parameters are also developed to account for proximity effects in some alkanolamines. A combination of literature data and new experimental measurements for the absorption of CO2 in aqueous cyclohexylamine systems obtained in our current work, are used to develop and test the proposed models. The SAFT-
Mie GC approach is used to predict the thermodynamics of selected mixtures, including ternary phase diagrams and mixing properties relevant in the context of CO2 capture. The current work constitutes a substantial extension of the range of aqueous amine-based solvents that can be modelled and thus offers the most comprehensive thermodynamically consistent platform to date to screen novel candidate solvents for CO2 capture.
) capture by chemisorption. We develop a predictive framework that is applicable to aqueous solvent + CO
mixtures containing cyclic amines, alkyl polyamines, and alkanolamines. A number of the mixtures studied exhibit liquid–liquid phase separation, a behaviour that has shown promise in reducing the energetic cost of CO
capture. The proposed framework is based on the SAFT-
Mie group-contribution (GC) approach, in which chemical reactions are described via physical association models that allow a simpler, implicit, treatment of the chemical speciation characteristic of these mixtures. We use previously optimized group interaction parameters between some amine groups and water (Perdomo et al., 2021), and develop new group interactions for the cNH, cN, NH2, NH, N, cCHNH, and cCHN groups with CO2; a set of second-order group parameters are also developed to account for proximity effects in some alkanolamines. A combination of literature data and new experimental measurements for the absorption of CO2 in aqueous cyclohexylamine systems obtained in our current work, are used to develop and test the proposed models. The SAFT-
Mie GC approach is used to predict the thermodynamics of selected mixtures, including ternary phase diagrams and mixing properties relevant in the context of CO2 capture. The current work constitutes a substantial extension of the range of aqueous amine-based solvents that can be modelled and thus offers the most comprehensive thermodynamically consistent platform to date to screen novel candidate solvents for CO2 capture.
Date Issued
2023-03
Date Acceptance
2022-10-13
Citation
Fluid Phase Equilibria, 2023, 566, pp.1-27
ISSN
0378-3812
Publisher
Elsevier BV
Start Page
1
End Page
27
Journal / Book Title
Fluid Phase Equilibria
Volume
566
Copyright Statement
© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S0378381222002540?via%3Dihub
Publication Status
Published
Article Number
113635
Date Publish Online
2022-10-19