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An Easy-to-Use Tool for Modeling the Dynamics of Capacitive Deionization
KTH, School of Engineering Sciences (SCI), Applied Physics.
KTH, School of Engineering Sciences (SCI), Applied Physics.
KTH, School of Engineering Sciences (SCI), Applied Physics.ORCID iD: 0000-0002-0074-3504
2019 (English)In: Journal of Physical Chemistry A, ISSN 1089-5639, E-ISSN 1520-5215, Vol. 123, no 30, p. 6628-6634Article in journal (Refereed) Published
Abstract [en]

Capacitive deionization is an emerging method of desalinating brackish water that has been presented as an alternative to the widely applied technologies such as reverse osmosis. However, for the technology to find more widespread use, it is important not only to improve its efficiency but also to make its modeling more accessible for researchers. In this work, a program has been developed and provided as an open-source with which a user can simulate the performance of a capacitive deionization system by simply entering the basic experimental conditions. The usefulness of this program was demonstrated by predicting how the effluent concentration in a continuous-mode constant-voltage operation varies with time, as well as how it depends on the flow rate, applied voltage, and inlet ion concentration. Finally, the generality of the program has been demonstrated using data from reports in the literature wherein various electrode materials, cell structures, and operational modes were used. Thus, we conclude that the model, termed the dynamic Langmuir model, could be an effective and simple tool for modeling the dynamics of capacitive deionization.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2019. Vol. 123, no 30, p. 6628-6634
National Category
Nano Technology
Identifiers
URN: urn:nbn:se:kth:diva-255149DOI: 10.1021/acs.jpca.9b05503ISI: 000486361700025Scopus ID: 2-s2.0-85070536289OAI: oai:DiVA.org:kth-255149DiVA, id: diva2:1338452
Note

QC 20190819

Available from: 2019-07-22 Created: 2019-07-22 Last updated: 2019-10-04Bibliographically approved

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Nordstrand, JohanLaxman, KarthikDutta, Joydeep

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