Ledingham, J., Sedransk Campbell, K.L., in ’t Veen, B. et al. (3 more authors) (2024) The development and validation of a novel, parameter-free, modelling strategy for electromembrane processes: Electrodialysis. Desalination, 576. 117386. ISSN 0011-9164
Abstract
As the global water crisis worsens and natural resources of strategic inorganic elements dwindle, the need for efficient and effective salt separation methods is becoming ever more important. Electromembrane processes, and in particular electrodialysis, are emerging as efficient and effective separation technologies that use an electric field to drive the transport of ions against a concentration gradient. Modelling electromembrane processes allows for process design and optimisation, as well as the identification of what technological improvements would have the greatest effect. However, the wide use of empirical fitting parameters in most existing models greatly limits their globality. The presence of complex and confounding phenomena within electromembrane processes greatly exacerbates this. In this work, a novel, circuit-based modelling strategy for electromembrane processes is presented, avoiding the use of any fitting parameters. Conventional electrodialysis is adopted as a case study. The implementation of a novel transport number model and membrane resistance model are crucial for model accuracy over a wide range of process conditions. The model was experimentally validated and showed excellent agreement with experimental data across a range of concentrations and voltages. Consequently, this model will prove to be an excellent tool for researchers and process designers.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Electrodialysis; Electromembrane separations; Process modelling; Ion exchange membranes |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > School of Chemical, Materials and Biological Engineering |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/T517835/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Sep 2024 10:15 |
Last Modified: | 06 Sep 2024 10:15 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.desal.2024.117386 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216909 |