Estimation of CO<inf>2</inf> Absorption by a Hybrid Aqueous Solution of Amino Acid Salt with Amine

Amirkhani, F; Dashti, A; Abedsoltan, H; Mohammadi, AH

Estimation of CO<inf>2</inf> Absorption by a Hybrid Aqueous Solution of Amino Acid Salt with Amine

Amirkhani, F Dashti, A

Abedsoltan, H Mohammadi, AH

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Publisher:: WILEY-V C H VERLAG GMBH
Publication Type:: Journal Article
Citation:: Chemical Engineering and Technology, 2024, 47, (2), pp. 253-261
Issue Date:: 2024-02-01

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Field	Value	Language
dc.contributor.author	Amirkhani, F
dc.contributor.author	Dashti, A https://orcid.org/0000-0002-3937-7353
dc.contributor.author	Abedsoltan, H
dc.contributor.author	Mohammadi, AH
dc.date.accessioned	2025-04-04T04:10:04Z
dc.date.available	2025-04-04T04:10:04Z
dc.date.issued	2024-02-01
dc.identifier.citation	Chemical Engineering and Technology, 2024, 47, (2), pp. 253-261
dc.identifier.issn	0930-7516
dc.identifier.issn	1521-4125
dc.identifier.uri	http://hdl.handle.net/10453/186603
dc.description.abstract	Four developed machine learning algorithms are proposed to prognosticate the CO2 solubility in amino acid salt solutions, blended with amine solutions as additives, in broad ranges of temperature and pressure. From literature 375 experimental data points for CO2 solubility were collected. The results from the applied algorithms indicated that the CO2 solubility is estimated acceptably close to the experimental values. In the best case, the developed network estimates CO2 solubility in the stated solutions with an average relative deviation of 6.53 % and a correlation coefficient of 0.9892.
dc.language	English
dc.publisher	WILEY-V C H VERLAG GMBH
dc.relation.ispartof	Chemical Engineering and Technology
dc.relation.isbasedon	10.1002/ceat.202200469
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0904 Chemical Engineering, 0913 Mechanical Engineering, 0915 Interdisciplinary Engineering
dc.subject.classification	Chemical Engineering
dc.subject.classification	4004 Chemical engineering
dc.subject.classification	4017 Mechanical engineering
dc.title	Estimation of CO<inf>2</inf> Absorption by a Hybrid Aqueous Solution of Amino Acid Salt with Amine
dc.type	Journal Article
utslib.citation.volume	47
utslib.for	0904 Chemical Engineering
utslib.for	0913 Mechanical Engineering
utslib.for	0915 Interdisciplinary Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2025-04-04T04:10:03Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	47
utslib.citation.issue	2

Abstract:

Four developed machine learning algorithms are proposed to prognosticate the CO2 solubility in amino acid salt solutions, blended with amine solutions as additives, in broad ranges of temperature and pressure. From literature 375 experimental data points for CO2 solubility were collected. The results from the applied algorithms indicated that the CO2 solubility is estimated acceptably close to the experimental values. In the best case, the developed network estimates CO2 solubility in the stated solutions with an average relative deviation of 6.53 % and a correlation coefficient of 0.9892.

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http://hdl.handle.net/10453/186603