MétaCan
Menu
Back to cohort
Record W4408783477 · doi:10.1021/acscatal.4c08113

Steering the Selectivity of Electrochemical CO<sub>2</sub> Reduction on the Cu Catalyst via the Interplay between the Electrode Morphology and Electrolyte Anion Identity

2025· article· en· W4408783477 on OpenAlexafffund
Cornelius A. Obasanjo, Gelson T. S. T. da Silva, Lúcia H. Mascaro, Cao‐Thang Dinh

Bibliographic record

VenueACS Catalysis · 2025
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaFundação Amazônia Paraense de Amparo à Pesquisa
KeywordsElectrochemistrySelectivityCatalysisElectrodeElectrolyteMorphology (biology)ElectrocatalystReduction (mathematics)Inorganic chemistryIonChemistryMaterials scienceSupporting electrolyteChemical engineeringOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Electrochemical carbon dioxide (CO 2 ) reduction (ECR) holds promise as a viable pathway for the generation of fuels and chemicals. Several strategies have been explored to enhance the product selectivity of ECR on copper (Cu) catalysts. A systematic approach to optimize the local reaction microenvironment, however, remains elusive. Engineering the electrode structure and reaction microenvironment is a facile but effective strategy for steering the product selectivity of ECR reactions and can enable the rational design of highly selective Cu electrodes. Herein, we demonstrate that the synergy between an optimized Cu gas diffusion electrode (GDE) morphology and electrolyte anion identity can steer ECR product selectivity toward ethylene (C 2+ ) or methane via the local CO 2 availability, pH, and electrode morphology regulation. We show that using a relatively thin 100 nm Cu catalyst layer (CL) sputtered on an optimized macropore-sized hydrophobic poly(tetrafluoroethylene) substrate promotes methane selectivity at high reaction rates. We achieved a methane partial current density of 126 mA cm –2 and a Faradaic efficiency (FE) of 42%. In contrast, a relatively thick 500 nm Cu CL favors ethylene production, reaching a high FE of 52% at 250 mA cm –2 (with a total C 2+ value of 77%) in a near-neutral KHCO 3 electrolyte. Utilizing KI electrolyte significantly enhances methane selectivity, achieving ca. 56% at a partial current density of 168 mA cm –2 while effectively suppressing the hydrogen evolution reaction (HER) on the thin CL. Furthermore, on the relatively thick CL, a higher C 2+ FE of 84% was achieved at 250 mA cm –2, demonstrating the impact of electrolyte anion identity and CL thickness on product selectivity in ECR. In addition, we find that a further increase in the Cu CL thickness does not result in a superior C 2+ performance in KI compared to the KHCO 3 electrolyte. Our result highlights the critical role of the interplay between Cu electrode morphology and the electrolyte anion identity, which can facilitate efficient CO 2 mass transport, enable selective Cu sites, and tune local pH – thereby steering ECR product selectivity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.018
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.255
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueACS CatalysisSame topicCO2 Reduction Techniques and CatalystsFrench-language works237,207