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Record W4386305277 · doi:10.1002/smll.202304081

Construction of Co<sub>2</sub>P‐Ni<sub>3</sub>S<sub>2</sub>/NF Heterogeneous Structural Hollow Nanowires as Bifunctional Electrocatalysts for Efficient Overall Water Splitting

2023· article· en· W4386305277 on OpenAlexafffund
Hangxuan Li, Xiaolan Gao, Ge Li

Bibliographic record

VenueSmall · 2023
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesCanada First Research Excellence FundUniversity of Alberta
KeywordsBifunctionalWater splittingMaterials scienceTransition metalNanowireNickelElectrocatalystNanotechnologyChemical engineeringCatalysisElectrolysisElectrodeOverpotentialElectrochemistryChemistryMetallurgyPhysical chemistryElectrolyte

Abstract

fetched live from OpenAlex

Abstract Designing efficient and stable transition metal‐based catalysts for electrocatalytic water splitting is vital for the development of hydrogen production. Herein, a facile synthetic strategy is developed to fabricate transition metal‐based heterogeneous structural Co 2 P‐Ni 3 S 2 hollow nanowires supported on nickel foam (Co 2 P‐Ni 3 S 2 /NF). Owing to the multiple active sites provided by transition metal compounds, large surface area of the unique hollow nanowire morphology, and the synergistic effect of Co 2 P‐Ni 3 S 2 heterostructure interfaces, Co 2 P‐Ni 3 S 2 /NF requires ultralow overpotentials of 110, 164 mV for HER and 331.7, 358.3 mV for OER at large current densities of 100, 500 mA cm −2 in alkaline medium, respectively. Importantly, the two‐electrode electrolyzer assembled by Co 2 P‐Ni 3 S 2 /NF displays a cell voltage of 1.54 V at 10 mA cm −2 and operates stably over 24 h at 100 mA cm −2 , which performs better than reported transition metal‐based bifunctional electrocatalysts. This work presents a successful fabrication of transition metal‐based bifunctional HER/OER electrocatalysts at large‐current density and brings new inspiration for developing applicable energy conversion materials.

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 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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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

Citations30
Published2023
Admission routes2
Has abstractyes

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