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Record W3118995302 · doi:10.1021/acs.jpcc.0c08854

Quantum Chemical Modeling of Oxygen Evolution Reaction Pathways Mediated by Metal (Oxy)hydroxide Complexes

2021· article· en· W3118995302 on OpenAlexafffund
Niranji Thilini Ekanayake, Shideh Ahmadi, Nicholas J. Mosey

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2021
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOxygen evolutionHydroxideCatalysisWater splittingMetalQuantum chemicalTransition metalChemistryOxygenMaterials scienceInorganic chemistryMoleculePhysical chemistryOrganic chemistryElectrochemistryPhotocatalysis

Abstract

fetched live from OpenAlex

The need for clean forms of renewable energy has provided the impetus to use H 2 as an energy storage material and fuel. A common approach to forming H 2 involves splitting water. The ability to convert water into hydrogen is limited by the oxygen evolution reaction (OER), which is one of two half-reactions involved in this process. The present study uses quantum chemical calculations to explore the abilities of a metal (oxy)hydroxide complex containing one to three earth-abundant first-row transition metals (Co, Fe, Ni, Mn, Ti) to catalyze the OER. The calculations provide insight into the mechanistic details of this process and the impacts of the coordination environment and substituting metal atoms on the ability to catalyze the OER. The results presented are expected to provide guidance for the rational design of advanced and effective metal catalysts for OER.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.215
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry C→Same topicElectrocatalysts for Energy Conversion→French-language works237,207→