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Record W4414024042 · doi:10.1021/acsnano.5c09554

Steering CO<sub>2</sub> Electroreduction Pathway via Tuning Microenvironment of Cobalt Center in Molecular Catalysts

2025· article· en· W4414024042 on OpenAlexafffund
Mingjie Wu, Siyi Yang, Yang Gao, Zhangsen Chen, Fang Dong, Huiyu Lei, Yingkui Yang, Ning Chen, Sasha Omanovic, Tom Regier, Xun Cui, Bao Yu Xia, Gaixia Zhang, Shuhui Sun

Bibliographic record

VenueACS Nano · 2025
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsÉcole de Technologie SupérieureCanadian Light Source (Canada)McGill UniversityInstitut National de la Recherche Scientifique
FundersScience and Technology Department of Hubei ProvinceNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Foundation for Innovation
KeywordsCobaltCatalysisMaterials scienceCenter (category theory)ChemistryNanotechnologyInorganic chemistryCrystallographyOrganic chemistry

Abstract

fetched live from OpenAlex

Owing to its chemical stability and molecular-level structural tunability, the molecular electrocatalyst cobalt phthalocyanine (CoPc) demonstrates significant potential for the electrochemical reduction of CO 2 (CO 2 RR). However, the specific catalytic reaction process of CO 2 RR and the dynamic structural evolution mechanisms of CoPc remain a contentious subject. Elucidating the reaction pathways of CO 2 electroreduction to CO and tracking structural evolution pose substantial challenges. In this study, we first used density functional theory (DFT) calculations to reveal the sequential proton–electron transfer (SPET) mechanisms for CO 2 RR on CoPc. Moreover, in situ X-ray absorption spectroscopy (XAS) elucidated a detailed deactivation mechanism, providing insights into the transition from single atomic sites (SAs) to nitrogen-coordinated nanoclusters (NCs) during CO 2 reduction. Based on these insights, we modified the pendant groups by introducing electron-withdrawing fluorine groups to change the reaction pathways of [*-COOH] 2– to the concerted proton–electron transfer (CPET) process, thereby effectively promoting the CO 2 electroreduction to CO. The presence of electron-withdrawing fluorine groups triggers central electron delocalization within CoPc, effectively mitigating the demetalation effect and enhancing the electron donation ability of Co active sites. As a result, we observed a markedly enhanced CO 2 RR performance, exhibiting high stability, activity, and FE CO compared to unmodified CoPc. This study contributes to the broader understanding of designing efficient molecular electrocatalysts for CO 2 RR.

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 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 score0.033
Threshold uncertainty score0.751

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 head0.004
GPT teacher head0.210
Teacher spread0.206 · 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

Citations6
Published2025
Admission routes2
Has abstractyes

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