MétaCan
Menu
Back to cohort
Record W3133711973 · doi:10.1002/aenm.202003511

Phase‐Separated Mo–Ni Alloy for Hydrogen Oxidation and Evolution Reactions with High Activity and Enhanced Stability

2021· article· en· W3133711973 on OpenAlexaff
Jidong Song, Yan Jin, Lei Zhang, Pengyu Dong, Jiawang Li, Fangyan Xie, Hao Zhang, Jian Chen, Yanshuo Jin, Hui Meng, Xueliang Sun

Bibliographic record

VenueAdvanced Energy Materials · 2021
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern University
FundersFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceAlloyExchange current densityIntermetallicCatalysisDensity functional theoryHydrogenReversible hydrogen electrodeElectrochemistryElectrolyteBimetallic stripNanoparticleElectron transferMetalChemical engineeringInorganic chemistryPhysical chemistryElectrodeNanotechnologyMetallurgyWorking electrodeChemistry

Abstract

fetched live from OpenAlex

Abstract The development of alkaline polymer electrolyte fuel cells and alkaline water electrolysis requires nonprecious metal catalysts for the hydrogen oxidation reaction (HOR) and hydrogen evolution reaction (HER). Herein, it is reported a phase‐separated Mo–Ni alloy (PS‐MoNi) that is composed of Mo metal and embedded Ni metal nanoparticles. The PS‐MoNi shows excellent hydrogen electrode activity with a high exchange current density (−4.883 mA cm −2 ), which is comparable to the reported highest value for non‐noble catalysts. Moreover, the amorphous phase‐separated Mo–Ni alloy has better structural and electrochemical stability than the intermetallic compound Mo–Ni alloy (IC‐MoNi). The breakdown potential of PS‐MoNi is as high as 0.32 V, which is much higher than that of reported IC‐MoNi. The X‐ray absorption near edge structure (XANES) and density functional theory (DFT) calculations indicate the electrons transfer from Mo to Ni for PS‐MoNi, leading to suitable adsorption free energies of H* (Δ G H* ) on the surface of Mo. This means that the electron density modulation of Mo metal by embedded Ni metal nanoparticles can produce excellent HOR and HER 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 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 score0.015
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.241
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.

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

Citations128
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Energy MaterialsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207