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Record W4210541923 · doi:10.1002/adma.202107053

Highly Active and Durable Single‐Atom Tungsten‐Doped NiS<sub>0.5</sub>Se<sub>0.5</sub> Nanosheet @ NiS<sub>0.5</sub>Se<sub>0.5</sub> Nanorod Heterostructures for Water Splitting

2022· article· en· W4210541923 on OpenAlexaff
Yang Wang, Xiaopeng Li, Mengmeng Zhang, Jinfeng Zhang, Zelin Chen, Xuerong Zheng, Zhangliu Tian, Naiqin Zhao, Xiaopeng Han, Karim Zaghib, Yuesheng Wang, Yida Deng, Wenbin Hu

Bibliographic record

VenueAdvanced Materials · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsHydro-Québec
FundersNational Natural Science Foundation of China
KeywordsNanosheetMaterials scienceElectrocatalystOxygen evolutionWater splittingNanorodChemical engineeringNanotechnologyCatalysisPhysical chemistryElectrochemistryChemistryPhotocatalysis

Abstract

fetched live from OpenAlex

Abstract Developing robust and highly active non‐precious electrocatalysts for the hydrogen/oxygen evolution reaction (HER/OER) is crucial for the industrialization of hydrogen energy. In this study, a highly active and durable single‐atom W‐doped NiS 0.5 Se 0.5 nanosheet @ NiS 0.5 Se 0.5 nanorod heterostructure (W‐NiS 0.5 Se 0.5 ) electrocatalyst is prepared. W‐NiS 0.5 Se 0.5 exhibits excellent catalytic activity for the HER and OER with ultralow overpotentials (39 and 106 mV for the HER and 171 and 239 mV for the OER at 10 and 100 mA cm −2 , respectively) and excellent long‐term durability (500 h), outperforming commercial precious‐metal catalysts and many other previously reported transition‐metal‐based compounds (TMCs). The introduction of single‐atom W delocalizes the spin state of Ni, which results in an increase in the Ni d‐electron density. This causes the optimization of the adsorption/desorption process of H and a significant reduction in the adsorption free energy of the rate‐determining step (O* → OOH*), thus accelerating the thermodynamics and kinetics of the HER and OER. This work provides a rational feasible strategy to design single‐atom catalysts for water splitting and to develop advanced TMC electrocatalysts by regulating delocalized spin states.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesMeta-epidemiology (narrow)
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 score0.013
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.003
Open science0.0020.002
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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

Citations240
Published2022
Admission routes1
Has abstractyes

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