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Record W4318947481 · doi:10.1149/1945-7111/acb84a

Novel Mechanically-Alloyed Cu–La–P Ternary Alloy Electrocatalysts for the Alkaline Hydrogen Evolution Reaction

2023· article· en· W4318947481 on OpenAlexafffund
Arthur D. Sloan, Rameez Ahmad Mir, Steven J. Thorpe

Bibliographic record

VenueJournal of The Electrochemical Society · 2023
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTafel equationOverpotentialIntermetallicPhosphideElectrocatalystMaterials scienceExchange current densityTernary operationTransition metalAlloyElectrochemistryCatalysisChemical engineeringMetallurgyInorganic chemistryMetalChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Transition metal phosphides, such as Cu3P, are of research interest as hydrogen evolution electrocatalysts due to a combination of good intrinsic activity and good stability. Rare earth-transition metal alloying is known to improve electrocatalytic performance, especially by the formation of intermetallic phases. Current transition metal phosphide electrocatalyst manufacturing methods are not capable of forming these intermetallic phases. Mechanical alloying is a promising technique to synthesize these intermetallic phases. Alloy powders of Cu3P, Cu19La5P12, and a novel multi-phase Cu74La4P22 composition were prepared using mechanical alloying and evaluated as electrocatalysts for the alkaline hydrogen evolution reaction on a geometric and intrinsic area basis. On an intrinsic basis, the novel Cu–La–P composition demonstrated excellent Tafel performance of 69.4 mV dec−1. Tafel slope, exchange current density, and overpotential data demonstrated the importance of spillover effects in multiphase Cu3P/Cu19La5P12 surface structures. These results suggest that Cu–La–P alloys are promising potential catalysts for electrochemical hydrogen production, and mechanical alloying of rare earth elements is an effective technique for improving the electrochemical performance of transition metal phosphides.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.234
Teacher spread0.225 · 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 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical Society→Same topicElectrocatalysts for Energy Conversion→French-language works237,207→