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Energy Efficiency of Capacitive Deionization

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Wang, Li, Dykstra, J. E., Lin, Shihong·2019·Environmental Science & Technology

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Abstract

Capacitive deionization (CDI) as a class of electrochemical desalination has attracted fast-growing research interest in recent years. A significant part of this growing interest is arguably attributable to the premise that CDI is energy efficient and has the potential to outcompete other conventional desalination technologies. In this review, systematic evaluation of literature data reveals that while the absolute energy consumption of CDI is in general low, most existing CDI systems achieve limited energy efficiency from a thermodynamic perspective. We also analyze the causes for the relatively low energy efficiency and discuss factors that may lead to enhanced energy efficiency for CDI.

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Authors: Wang, L., Dykstra, J. E., & Lin, S.
Venue: Environmental Science & Technology
Publisher: American Chemical Society (ACS)
Published: 2019-02-25
Volume: 53
Issue: 7
Pages: 3366-3378
ISSN: 0013-936X (ISSN-L)
1520-5851
DOI: 10.1021/acs.est.8b04858
OpenAlex: W2915403665
Cited by: 292
References: 95
FWCI: 11.28
Type: journal article
Language: en
Open access: green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.

Energy Efficiency of Capacitive Deionization

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Self-check

Citations

Cites

Cited by

Metadata

Record

About these checks

Data sources