Evidence map›Paper›PMID 41169674›Full record

ReviewScience and technology of advanced materials2025

Capacitive deionisation for water desalination review: experimental and simulation.

Rokhsareh Akbarzadeh, Mathias Ernst, Robert Meißner, Bodo Fiedler

Abstract readReview
In one paragraph

Review in Science and technology of advanced materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rokhsareh AkbarzadehInstitute of Polymers and Composites, Hamburg University of Technology, Hamburg, Germany.ORCID https://orcid.org/0000-0002-9934-6225
Mathias ErnstInstitute for Water Resources and Water Supply, Hamburg University of Technology, Hamburg, Germany.ORCID https://orcid.org/0000-0001-9282-6683
Robert MeißnerInstitute of Soft Matter Modeling, Hamburg University of Technology, Hamburg, Germany.ORCID https://orcid.org/0000-0003-1926-114X
Bodo FiedlerInstitute of Polymers and Composites, Hamburg University of Technology, Hamburg, Germany.ORCID https://orcid.org/0000-0002-2734-1353

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Capacitive Deionization (CDI) has emerged as an energy-efficient and environmentally friendly technology for water desalination. This review provides a comprehensive analysis of CDI, covering both experimental and simulation approaches. It introduces the background, definition, and diverse applications of CDI, from water desalination to environmental monitoring and resource recovery. The review highlights CDI's advantages, such as low energy consumption and operational simplicity, as well as its limitations, particularly its design-specific operating window favoring low-to-moderate salinity waters and sensitivity to organic-rich conditions. Strategies such as hybrid CDI systems and electrode surface functionalization are discussed to mitigate these challenges. Key working principles and advancements, including innovations in electrode materials, synthesis methods, and reactor design, are examined to improve ion removal efficiency, selectivity, energy use, and system durability. Material modification strategies are presented in the context of structure - performance relationships, emphasizing rational design principles. The review also explores simulation methods, including reactor modeling, computational fluid dynamics, molecular dynamics, and numerical approaches, and machine learning highlighting their synergy with experiments in optimizing CDI performance and guiding scale-up. Coupling CDI with other systems and its applications in water purification, particularly for ion and organic compound removal are also discussed. Finally, challenges in both experimental and simulation efforts, such as material cost, model complexity, computational demands, and scalability, are discussed. While CDI shows promise for sustainable water desalination and resource recovery, further research on hybrid configurations, predictive modeling, and pilot-scale validation is needed to address its limitations and enable large-scale adoption.

Indexed as

Capacitive deionisation (CDI)desalinationelectrosorptionFCDIion removalMCDIsimulation

Identifiers

PMID41169674
PMCPMC12570255

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.