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Record W3122912485 · doi:10.1038/s41467-020-20615-0

The nature of active sites for carbon dioxide electroreduction over oxide-derived copper catalysts

2021· article· en· W3122912485 on OpenAlexaff
Dongfang Cheng, Zhi‐Jian Zhao, Gong Zhang, Piaoping Yang, Lulu Li, Hui Gao, Sihang Liu, Xin Chang, Sai Chen, Tuo Wang, Geoffrey A. Ozin, Zhi‐Pan Liu, Jinlong Gong

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaTianjin UniversityNational Natural Science Foundation of ChinaProject 211National Science Foundation
KeywordsCatalysisCopperOxideDensity functional theoryActive siteChemistrySelectivityMaterials scienceInorganic chemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The active sites for CO 2 electroreduction (CO 2 R) to multi-carbon (C 2+ ) products over oxide-derived copper (OD-Cu) catalysts are under long-term intense debate. This paper describes the atomic structure motifs for product-specific active sites on OD-Cu catalysts in CO 2 R. Herein, we describe realistic OD-Cu surface models by simulating the oxide-derived process via the molecular dynamic simulation with neural network (NN) potential. After the analysis of over 150 surface sites through NN potential based high-throughput testing, coupled with density functional theory calculations, three square-like sites for C–C coupling are identified. Among them, Σ3 grain boundary like planar-square sites and convex-square sites are responsible for ethylene production while step-square sites, i.e. n (111) × (100), favor alcohols generation, due to the geometric effect for stabilizing acetaldehyde intermediates and destabilizing Cu–O interactions, which are quantitatively demonstrated by combined theoretical and experimental results. This finding provides fundamental insights into the origin of activity and selectivity over Cu-based catalysts and illustrates the value of our research framework in identifying active sites for complex heterogeneous catalysts.

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 score0.134
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.293
Teacher spread0.281 · 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

Citations315
Published2021
Admission routes1
Has abstractyes

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