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Record W4415213415 · doi:10.1002/aenm.202502564

Integrated Carbon Dioxide Capture and Electrochemical Conversion: Chemistry, Electrode and Electrolyzer Design, and Economic Viability

2025· article· en· W4415213415 on OpenAlexaff
Behnam Nourmohammadi Khiarak, Gelson T. S. T. da Silva, Hossein Esmaeili, Anh Ngoc Nguyen, Khac‐Huy Dinh, Qian Zhang, Lúcia H. Mascaro, Cao‐Thang Dinh

Bibliographic record

VenueAdvanced Energy Materials · 2025
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsQueen's University
Fundersnot available
KeywordsElectrochemistryElectrolysisCarbon dioxideCarbonationRenewable energyElectrochemical cellCarbon fibers

Abstract

fetched live from OpenAlex

Abstract Electrochemical carbon dioxide (CO 2 ) conversion (ECC) offers a promising route to reduce CO 2 emissions and to store renewable electricity in the form of chemical fuels. To date, ECC has been mainly based on pure CO 2 gas isolated from carbon capture solutions, which is an energy‐intensive step. Recently, direct CO 2 conversion from a capture solution, which enables integrated CO 2 capture and electrochemical conversion, has attracted attention because it can eliminate the energy‐intensive CO 2 isolation step. In addition, producing concentrated gas products in integrated systems reduces the cost for downstream separation. This review discusses the key aspects of integrated CO 2 capture and electrochemical conversion systems, including direct air capture (DAC), the chemistry of CO 2 capture and release, electrode designs and system configurations, as well as technoeconomic viability. First, the fundamental concepts and chemistry of CO 2 capture and in situ CO 2 release in electrochemical reactors are summarized. Then, recent advancements in integrated systems are discussed, covering both system configurations and electrode designs. Potential avenues for enhancing product selectivity toward high‐value chemicals, such as ethylene and ethanol, as well as lowering operating cell voltages and improving the economic viability of integrated systems, are highlighted. Finally, major technical and economic challenges as well as emerging research opportunities in the domain of integrated CO 2 capture and conversion are highlighted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.206
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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