MétaCan
Menu
Back to cohort
Record W4403954087 · doi:10.1002/smll.202407860

The Interfacial Ni/Fe─O─Y Bonds Contribute to High‐Efficiency Water Splitting

2024· article· en· W4403954087 on OpenAlexaff
Zhen Xin Hui, Hui Li, Zhiwen Chen, Zi Wen, Guoyong Wang, Chandra Veer Singh, Chun Cheng Yang, Qing Jiang

Bibliographic record

VenueSmall · 2024
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsOverpotentialDensity functional theoryWater splittingMaterials scienceDissociation (chemistry)Electrolysis of waterRaman spectroscopyOxygen evolutionHydrogenAdsorptionElectrolysisChemical engineeringPhysical chemistryElectrochemistryChemistryCatalysisComputational chemistryElectrode

Abstract

fetched live from OpenAlex

Abstract Developing economical and efficient electrocatalysts is critical for hydrogen energy industrialization through water electrolysis. Herein, a novel dual‐site synergistic NiFe/Y 2 O 3 hybrid with abundant interfacial Ni/Fe─O─Y bonds is designed by density functional theory (DFT) simulations. In situ Raman spectra combined with DFT calculations reveal that the interfacial Ni/Fe─O─Y units greatly promote H 2 O dissociation and optimize the adsorption of both H* and oxygen species, achieving excellent activity and durability for hydrogen evolution reaction. As expected, NiFe/Y 2 O 3 exhibits a low overpotential of 27 mV at 10 mA cm −2 and robust stability of over 200 h at 1000 mA cm −2 , and also outstanding water splitting performance with a low cell voltage of 1.64 V at 100 mA cm −2 , showing significant potential for real‐world applications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.002

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 head0.216
Teacher spread0.209 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueSmallSame topicElectrocatalysts for Energy ConversionFrench-language works237,207