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Record W2039558708 · doi:10.1149/05845.0067ecst

Photochemical Route for the Preparation of Complex Amorphous Water Oxidation Catalyst

2014· article· en· W2039558708 on OpenAlexafffund
Rodney D. L. Smith, Simon Trudel, Curtis P. Berlinguette

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaInstitut National Du Cancer
KeywordsAmorphous solidTafel equationOxideCatalysisMaterials scienceX-ray photoelectron spectroscopyTernary operationMetalInorganic chemistryChemical engineeringAmorphous metalElectrochemistryPhotochemistryChemistryPhysical chemistryElectrodeOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

A photochemically initiated decomposition reaction was used to synthesize a series of amorphous mixed-metal oxide films. The series, consisting of mixed-metal oxides included binary and ternary mixtures containing Fe, Co and/or Ni, enabled a systematic evaluation of amorphous metal oxides with complex compositions. X-ray diffraction results indicate that the as-deposited films are amorphous and can be converted to their crystalline form by heating. Infrared spectroscopy of the films indicates the photochemically driven process drives complete loss of the organic constituents from the film. X-ray photoelectron spectroscopy confirmed the loss of the organic ligand and enabled estimation of metal oxidation states. Electrochemical characterization revealed significant variation in catalytic performance toward the oxygen evolving reaction (OER) upon variation of metal oxide composition. Analysis of the Tafel behavior was used to distinguish amorphous mixed-metal oxide films to enable several film compositions to exhibit excellent electrocatalytic OER performance.

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: none
Teacher disagreement score0.651
Threshold uncertainty score0.314

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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