ArticleACS omega2025
Thermodynamic Evaluation of Electrode Storage for Capacitive Deionization.
Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study details the development of a computational adsorption model for predicting thermodynamic adsorption parameters for capacitive deionization (CDI) processes. To do this, multiple starting concentrations and temperatures are needed to predict the best fit value. This is first demonstrated experimentally using an in-house CDI cell with custom heaters, and determining maximum adsorption capabilities for a selected range of conditions. This has been done previously for CDI in the published literature, but here, experimental results are incorporated to provide the best fit to a computational model, which runs transient CDI tests in batch mode over multiple concentrations and temperatures to determine adsorption parameters. This saves the eventual challenge of having to run many different experiments independently to determine such adsorption parameters, the accuracy of which may be questionable subject to different experimental errors. With the model, many parameters can be quickly scanned at once, and adsorption parameters can be determined based on the concentration and temperature values selected, as well as other operating conditions, such as voltage and cell resistance. The computational isotherms are generated using the Gouy-Chapman-Stern (GCS) model, which is common for the lower concentration values used for CDI. The model also considers fixed and mobile chemical charges for enhanced CDI (ECDI) and Faradaic CDI (FaCDI), respectively, which have been examined as alternatives to improve CDI performance. While primarily proof-of-concept, the results obtained here demonstrate the benefits in adsorption capabilities, and energy savings obtained here demonstrate benefits in adsorption capabilities and energy savings for FaCDI, coinciding with higher enthalpies and entropies of adsorption. The model also serves as a benchmark in the future for how the results can be further explored and better fits can be obtained experimentally to confirm stability in the thermodynamic values.
Identifiers
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Registered trials
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