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Electrocatalysis of borohydride oxidation: a review of density functional theory approach combined with experimental validation

2014· review· en· W2033979411 on OpenAlexaff
Mary Clare Sison Escaño, Ryan Lacdao Arevalo, Előd Gyenge, Hideaki Kasai

Bibliographic record

VenueJournal of Physics Condensed Matter · 2014
Typereview
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBorohydrideElectrocatalystDensity functional theoryCatalysisChemistryFuel cellsAdsorptionComputational chemistryMaterials scienceCombinatorial chemistryElectrochemistryChemical engineeringPhysical chemistryOrganic chemistryElectrodeEngineering

Abstract

fetched live from OpenAlex

The electrocatalysis of borohydride oxidation is a complex, up-to-eight-electron transfer process, which is essential for development of efficient direct borohydride fuel cells. Here we review the progress achieved by density functional theory (DFT) calculations in explaining the adsorption of BH4(-) on various catalyst surfaces, with implications for electrocatalyst screening and selection. Wherever possible, we correlate the theoretical predictions with experimental findings, in order to validate the proposed models and to identify potential directions for further advancements.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.255
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2014
Admission routes1
Has abstractyes

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