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Record W4362506256 · doi:10.1021/jacs.2c12431

Doping Shortens the Metal/Metal Distance and Promotes OH Coverage in Non-Noble Acidic Oxygen Evolution Reaction Catalysts

2023· article· en· W4362506256 on OpenAlexafffund
Ning Wang, Pengfei Ou, Rui Kai Miao, Yuxin Chang, Ziyun Wang, Sung‐Fu Hung, Jehad Abed, Adnan Ozden, Hsuan‐Yu Chen, Heng‐Liang Wu, Jianan Erick Huang, Daojin Zhou, Weiyan Ni, Lizhou Fan, Yushan Yan, Tao Peng, David Sinton, Yongchang Liu, Hongyan Liang, Edward H. Sargent

Bibliographic record

VenueJournal of the American Chemical Society · 2023
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersNational Taiwan UniversityMinistry of Science and Technology, TaiwanUniversity of TorontoSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNatural Sciences and Engineering Research Council of CanadaNational Science and Technology CouncilMinistry of Education of the People's Republic of ChinaGovernment of OntarioNational Natural Science Foundation of ChinaNatural Resources CanadaCanada Foundation for InnovationOntario Research FoundationNational Science FoundationNGIF Capital Corporation
KeywordsChemistryCatalysisNoble metalElectrolysis of waterOverpotentialElectrolysisElectrolyteInorganic chemistryOxygen evolutionAdsorptionOxideMetalBulk electrolysisHydrogenPlatinumWater splittingElectrochemistryElectrodePhysical chemistryPhotocatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Acidic water electrolysis enables the production of hydrogen for use as a chemical and as a fuel. The acidic environment hinders water electrolysis on non-noble catalysts, a result of the sluggish kinetics associated with the adsorbate evolution mechanism, reliant as it is on four concerted proton-electron transfer steps. Enabling a faster mechanism with non-noble catalysts will help to further advance acidic water electrolysis. Here, we report evidence that doping Ba cations into a Co 3 O 4 framework to form Co 3– x Ba x O 4 promotes the oxide path mechanism and simultaneously improves activity in acidic electrolytes. Co 3– x Ba x O 4 catalysts reported herein exhibit an overpotential of 278 mV at 10 mA/cm 2 in 0.5 M H 2 SO 4 electrolyte and are stable over 110 h of continuous water oxidation operation. We find that the incorporation of Ba cations shortens the Co–Co distance and promotes OH adsorption, findings we link to improved water oxidation in acidic electrolyte.

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 score0.063
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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

Citations286
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicElectrocatalysts for Energy ConversionFrench-language works237,207