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Record W4311551357 · doi:10.1021/acscatal.2c04512

Cooperative Redox Transitions Drive Electrocatalysis of the Oxygen Evolution Reaction on Cobalt–Iron Core–Shell Nanoparticles

2022· article· en· W4311551357 on OpenAlexaff
Lisa Royer, Antoine Bonnefont, Tristan Asset, Benjamin Rotonnelli, Juan‐Jesús Velasco‐Vélez, Steven Holdcroft, Simón Hettler, Raúl Arenal, Benoît P. Pichon, Elena R. Savinova

Bibliographic record

VenueACS Catalysis · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsSimon Fraser University
FundersHorizon 2020 Framework ProgrammeMinisterio de Ciencia e InnovaciónGobierno de AragónFondation Pour la Recherche en ChimieGraphene Flagship
KeywordsXANESElectrocatalystOxygen evolutionRedoxCatalysisCobaltNanoparticleExtended X-ray absorption fine structureChemistryTransition metalInorganic chemistryElectron transferSpinelCobalt oxideOxideX-ray absorption spectroscopyAbsorption spectroscopyMaterials sciencePhotochemistrySpectroscopyElectrochemistryNanotechnologyPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Transition metal oxides are promising materials for the development of cost-effective catalysts for the oxygen evolution reaction (OER) in alkaline media. Understanding the catalysts’ transformations occurring during the harsh oxidative conditions of the OER remains a bottleneck for the development of stable and active catalysts. Here, we studied redox transformations of core–shell Fe3O4@CoFe2O4 oxide nanoparticles over a wide range of potentials by using operando near-edge X-ray absorption fine structure (NEXAFS) spectroscopy in total electron yield (TEY) detection mode. The analysis of the NEXAFS spectra reveals that the Fe3O4 core strongly affects the surface chemistry of the CoFe2O4 shell under the OER conditions. The spinel structure of the particles with Co (II) in the shell is preserved at potentials as high as 1.8 V vs RHE, at which Co (II) is expected to be oxidized into Co (III); whereas Fe (II) in the core is reversibly oxidized to Fe (III).

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 categoriesMeta-epidemiology (narrow)
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 score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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.

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

Citations26
Published2022
Admission routes1
Has abstractyes

Explore more

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