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Record W4200115287 · doi:10.1021/acsanm.1c03403

Eggshell-like MoS<sub>2</sub> Nanostructures with Negative Curvature and Stepped Faces for Efficient Hydrogen Evolution Reactions

2021· article· en· W4200115287 on OpenAlexaff
Jian Li, Li Xin Chen, Xiao Xuan Liu, Zi Wen, Chandra Veer Singh, Chun Cheng Yang, Qing Jiang

Bibliographic record

VenueACS Applied Nano Materials · 2021
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of ChinaNatural Science Foundation of Jilin Province
KeywordsOverpotentialCatalysisNanostructureMaterials sciencePorosityHydrogenNanotechnologyCurrent densityDensity functional theoryChemical engineeringCurvatureEggshellChemical physicsChemistryElectrodeComposite materialComputational chemistryElectrochemistryPhysical chemistryPhysicsGeometryOrganic chemistry

Abstract

fetched live from OpenAlex

As an alternative to the state-of-the-art Pt-based materials, MoS2 has attracted substantial attention as a hydrogen evolution reaction (HER) catalyst. In this study, density functional theory calculations reveal that negative curvature and stepped faces of MoS2 could weaken the hydrogen adsorption, leading to high intrinsic catalytic activity for HER. Based on this consideration, a MoS2 catalyst with an ultrathin eggshell-like nanostructure is designed and fabricated, where the uniform porous structure together with ultrathin layers exposes more active sites. Such a porous MoS2 catalyst exhibits an overpotential of 180 mV at a current density of −10 mA cm–2, outperforming most of the current MoS2 catalysts.

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 score0.014
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 communication0.0000.000
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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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