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Record W4291397349 · doi:10.1002/adma.202204476

Surface Co‐Modification of Halide Anions and Potassium Cations Promotes High‐Rate CO<sub>2</sub>‐to‐Ethanol Electrosynthesis

2022· article· en· W4291397349 on OpenAlexaff
Peng Chen, Songtao Yang, Gan Luo, Shuai Yan, Mohsen Shakouri, Junbo Zhang, Yangshen Chen, Weihan Li, Zhiqiang Wang, Tsun‐Kong Sham, Gengfeng Zheng

Bibliographic record

VenueAdvanced Materials · 2022
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsWestern UniversityCanadian Light Source (Canada)University of Saskatchewan
FundersNational Key Research and Development Program of ChinaScience and Technology Commission of Shanghai MunicipalityShanghai Municipal Education CommissionNational Natural Science Foundation of China
KeywordsElectrosynthesisElectrocatalystElectrochemistryFaraday efficiencyHalideMaterials scienceCatalysisInorganic chemistrySurface modificationFluorinePotassiumAlkali metalPhysical chemistryElectrodeChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The high‐rate electrochemical CO 2 conversion to ethanol with high partial current density is attractive but challenging, which requires competing with other reduction products as well as hydrogen evolution. This work demonstrates the in situ reconstruction of KCuF 3 perovskite under CO 2 electroreduction conditions to fabricate a surface fluorine‐bonded, single‐potassium‐atom‐modified Cu(111) nanocrystal (K–F–Cu–CO 2 ). Density functional theory calculations reveal that the co‐modification of both F and K atoms on the Cu(111) surface can promote the ethanol pathway via stabilization of the CO bond and selective hydrogenation of the CC bond in the CH 2 CHO* intermediate, while the single modification of either F or K is less effective. The K–F–Cu–CO 2 electrocatalyst exhibits an outstanding CO 2 ‐to‐ethanol partial current density of 423 ± 30 mA cm −2 with the corresponding Faradaic efficiency of 52.9 ± 3.7%, and a high electrochemical stability at large current densities, thus suggesting an attractive means of surface co‐modification of halide anions and alkali‐metal cations on Cu catalysts for high‐rate CO 2 ‐to‐ethanol electrosynthesis.

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 score0.005
Threshold uncertainty score0.705

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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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

Citations91
Published2022
Admission routes1
Has abstractyes

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