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Record W2914544678 · doi:10.1038/s41467-019-08419-3

Ruthenium atomically dispersed in carbon outperforms platinum toward hydrogen evolution in alkaline media

2019· article· en· W2914544678 on OpenAlexafffund
Bingzhang Lu, Lin Guo, Feng Wu, Yi Peng, Jia Lu, Tyler J. Smart, Nan Wang, Y. Zou Finfrock, David J. Morris, Peng Zhang, Ning Li, Peng Gao, Yuan Ping, Shaowei Chen

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsDalhousie UniversityCanadian Light Source (Canada)
FundersLawrence Berkeley National LaboratoryU.S. Department of EnergyBrookhaven National LaboratoryArgonne National LaboratoryDivision of ChemistryDivision of Materials ResearchOffice of ScienceTianjin UniversityDivision of Chemical, Bioengineering, Environmental, and Transport SystemsTianjin University of TechnologyCanadian Light SourceNational Science Foundation
KeywordsRutheniumOverpotentialCatalysisPlatinumHydrogenDissociation (chemistry)ElectrochemistryCarbon fibersMaterials scienceInorganic chemistryPlatinum nanoparticlesNanoparticleChemistryNanotechnologyPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Hydrogen evolution reaction is an important process in electrochemical energy technologies. Herein, ruthenium and nitrogen codoped carbon nanowires are prepared as effective hydrogen evolution catalysts. The catalytic performance is markedly better than that of commercial platinum catalyst, with an overpotential of only −12 mV to reach the current density of 10 mV cm -2 in 1 M KOH and −47 mV in 0.1 M KOH. Comparisons with control experiments suggest that the remarkable activity is mainly ascribed to individual ruthenium atoms embedded within the carbon matrix, with minimal contributions from ruthenium nanoparticles. Consistent results are obtained in first-principles calculations, where RuC x N y moieties are found to show a much lower hydrogen binding energy than ruthenium nanoparticles, and a lower kinetic barrier for water dissociation than platinum. Among these, RuC 2 N 2 stands out as the most active catalytic center, where both ruthenium and adjacent carbon atoms are the possible active sites.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.238
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations612
Published2019
Admission routes2
Has abstractyes

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