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An exergy-guided thermodynamic framework for the optimization of electro-membrane-based coupled process.

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Title: An exergy-guided thermodynamic framework for the optimization of electro-membrane-based coupled process.
Authors: Shen, Ruochen1 (AUTHOR), Du, Yawei1,2 (AUTHOR), Wang, Lurong1 (AUTHOR), Sun, Mengmeng1,2,3 (AUTHOR), Chen, Tianyi1 (AUTHOR), Wang, Shizhao1,2,3 (AUTHOR), Bi, Jingtao1,2,3 (AUTHOR), Li, Wenhao4 (AUTHOR), Liu, Jianlu4 (AUTHOR), Zhao, Yingying1,2,3,5 (AUTHOR) luckyzhaoyy@126.com
Source: Water Research. Jan2026:Part A, Vol. 288, pN.PAG-N.PAG. 1p.
Subjects: Exergy, Thermodynamics, Ion-permeable membranes, Energy dissipation, Mathematical optimization, Electrodialysis
Abstract: • A multi-variable optimization framework for electro-membrane coupled process. • In-depth analysis of exergy flow in BMED coupled flue gas treatment process. • Two critical energy losses identified: proton leakage & reaction irreversibility. Electrically driven membrane separation processes are extensively utilized in water treatment due to their remarkable flexibility, which facilitates seamless integration with a wide range of other processes. However, optimizing complex coupled systems, where transport phenomena are intertwined with chemical reactions, remains a grand challenge. Conventional performance metrics and existing thermodynamic models often fail to deconvolute the distinct sources of energy loss, hindering targeted improvements. To address this, we introduce a novel diagnostic framework that, for the first time, integrates transmembrane ionic exergy analysis with the exergy accounting of a coupled, multiphase reaction network. This allows for the explicit quantification of previously lumped thermodynamic irreversibility. Applying this framework to a bipolar membrane electrodialysis (BMED) system for flue-gas treatment, we identified and quantified two dominant, yet distinct, energy loss pathways: (1) proton (H+) leakage across the anion exchange membrane, a transport-related loss, and (2) the inherent irreversibility of the gas–liquid–solid reaction chain, a chemistry-related loss. Pinpointing these specific bottlenecks provides clear targets for optimization. The framework facilitates multi-objective optimization, identifying an operational region that balances performance with thermodynamic efficiency. Experimental results validate the model's ability to predict key operational trends with good quantitative accuracy. With its high adaptability, this exergy-guided diagnostic approach offers a powerful and generalizable tool for analyzing and optimizing complex electrochemical systems. [Display omitted] [ABSTRACT FROM AUTHOR]
Copyright of Water Research is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 189283402
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  Data: An exergy-guided thermodynamic framework for the optimization of electro-membrane-based coupled process.
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  Data: <searchLink fieldCode="AR" term="%22Shen%2C+Ruochen%22">Shen, Ruochen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Du%2C+Yawei%22">Du, Yawei</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Lurong%22">Wang, Lurong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Mengmeng%22">Sun, Mengmeng</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Tianyi%22">Chen, Tianyi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Shizhao%22">Wang, Shizhao</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bi%2C+Jingtao%22">Bi, Jingtao</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Wenhao%22">Li, Wenhao</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Jianlu%22">Liu, Jianlu</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Yingying%22">Zhao, Yingying</searchLink><relatesTo>1,2,3,5</relatesTo> (AUTHOR)<i> luckyzhaoyy@126.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Water+Research%22">Water Research</searchLink>. Jan2026:Part A, Vol. 288, pN.PAG-N.PAG. 1p.
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  Data: • A multi-variable optimization framework for electro-membrane coupled process. • In-depth analysis of exergy flow in BMED coupled flue gas treatment process. • Two critical energy losses identified: proton leakage & reaction irreversibility. Electrically driven membrane separation processes are extensively utilized in water treatment due to their remarkable flexibility, which facilitates seamless integration with a wide range of other processes. However, optimizing complex coupled systems, where transport phenomena are intertwined with chemical reactions, remains a grand challenge. Conventional performance metrics and existing thermodynamic models often fail to deconvolute the distinct sources of energy loss, hindering targeted improvements. To address this, we introduce a novel diagnostic framework that, for the first time, integrates transmembrane ionic exergy analysis with the exergy accounting of a coupled, multiphase reaction network. This allows for the explicit quantification of previously lumped thermodynamic irreversibility. Applying this framework to a bipolar membrane electrodialysis (BMED) system for flue-gas treatment, we identified and quantified two dominant, yet distinct, energy loss pathways: (1) proton (H+) leakage across the anion exchange membrane, a transport-related loss, and (2) the inherent irreversibility of the gas–liquid–solid reaction chain, a chemistry-related loss. Pinpointing these specific bottlenecks provides clear targets for optimization. The framework facilitates multi-objective optimization, identifying an operational region that balances performance with thermodynamic efficiency. Experimental results validate the model's ability to predict key operational trends with good quantitative accuracy. With its high adaptability, this exergy-guided diagnostic approach offers a powerful and generalizable tool for analyzing and optimizing complex electrochemical systems. [Display omitted] [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Water Research is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.watres.2025.124577
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Exergy
        Type: general
      – SubjectFull: Thermodynamics
        Type: general
      – SubjectFull: Ion-permeable membranes
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      – SubjectFull: Energy dissipation
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      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Electrodialysis
        Type: general
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      – TitleFull: An exergy-guided thermodynamic framework for the optimization of electro-membrane-based coupled process.
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            – D: 01
              M: 01
              Text: Jan2026:Part A
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              Y: 2026
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