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Record W4379768333 · doi:10.1038/s41467-023-38935-2

Single-site decorated copper enables energy- and carbon-efficient CO2 methanation in acidic conditions

2023· article· en· W4379768333 on OpenAlexafffund
Mengyang Fan, Rui Kai Miao, Pengfei Ou, Yi Xu, Zih‐Yi Lin, Tsung-Ju Lee, Sung‐Fu Hung, Ke Xie, Jianan Erick Huang, Weiyan Ni, Jun Li, Yong Zhao, Adnan Ozden, Colin P. O’Brien, Yuanjun Chen, Yurou Celine Xiao, Shijie Liu, Joshua Wicks, Xue Wang, Jehad Abed, Erfan Shirzadi, Edward H. Sargent, David Sinton

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Science and Technology CouncilGovernment of OntarioSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNatural Resources CanadaCanadian Light SourceNational Science Foundation
KeywordsEthylenediaminetetraacetic acidElectrocatalystCopperFaraday efficiencyChelationChemistryIonSelectivityCarbon fibersInorganic chemistryDenticityCatalysisTonneMaterials scienceElectrochemistryElectrodeMetalOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Renewable CH 4 produced from electrocatalytic CO 2 reduction is viewed as a sustainable and versatile energy carrier, compatible with existing infrastructure. However, conventional alkaline and neutral CO 2 -to-CH 4 systems suffer CO 2 loss to carbonates, and recovering the lost CO 2 requires input energy exceeding the heating value of the produced CH 4 . Here we pursue CH 4 -selective electrocatalysis in acidic conditions via a coordination method, stabilizing free Cu ions by bonding Cu with multidentate donor sites. We find that hexadentate donor sites in ethylenediaminetetraacetic acid enable the chelation of Cu ions, regulating Cu cluster size and forming Cu-N/O single sites that achieve high CH 4 selectivity in acidic conditions. We report a CH 4 Faradaic efficiency of 71% (at 100 mA cm −2 ) with <3% loss in total input CO 2 that results in an overall energy intensity (254 GJ/tonne CH 4 ), half that of existing electroproduction routes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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 designNot applicable
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

Citations114
Published2023
Admission routes2
Has abstractyes

Explore more

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