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Record W3096113897 · doi:10.34133/2020/9167829

Oxygen Reduction Reaction Catalyzed by Carbon-Supported Platinum Few-Atom Clusters: Significant Enhancement by Doping of Atomic Cobalt

2020· article· en· W3096113897 on OpenAlex
Bingzhang Lu, Qiming Liu, Forrest Nichols, Rene Mercado, David J. Morris, Ning Li, Peng Zhang, Peng Gao, Yuan Ping, Shaowei Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsDalhousie University
FundersDivision of ChemistryDivision of Materials ResearchNational Research Council CanadaGovernment of SaskatchewanWestern Economic Diversification CanadaCanadian Light SourceNatural Sciences and Engineering Research Council of CanadaOffice of ScienceNational Science FoundationCanadian Institutes of Health ResearchPeking UniversityNational Natural Science Foundation of ChinaUniversity of California, Santa CruzArgonne National LaboratoryU.S. Department of EnergyLawrence Berkeley National LaboratoryUniversity of Saskatchewan
KeywordsCatalysisPlatinumDopingNanoparticleMaterials scienceCobaltCarbon fibersOxygenElectrochemistryPhysical chemistryChemistryNanotechnologyMetallurgyElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Oxygen reduction reaction (ORR) plays an important role in dictating the performance of various electrochemical energy technologies. As platinum nanoparticles have served as the catalysts of choice towards ORR, minimizing the cost of the catalysts by diminishing the platinum nanoparticle size has become a critical route to advancing the technological development. Herein, first-principle calculations show that carbon-supported Pt 9 clusters represent the threshold domain size, and the ORR activity can be significantly improved by doping of adjacent cobalt atoms. This is confirmed experimentally, where platinum and cobalt are dispersed in nitrogen-doped carbon nanowires in varied forms, single atoms, few-atom clusters, and nanoparticles, depending on the initial feeds. The sample consisting primarily of Pt 2~7 clusters doped with atomic Co species exhibits the best mass activity among the series, with a current density of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>4.16</mml:mn> <mml:mtext> </mml:mtext> <mml:mtext>A</mml:mtext> <mml:mtext> </mml:mtext> <mml:msubsup> <mml:mrow> <mml:mtext>mg</mml:mtext> </mml:mrow> <mml:mrow> <mml:mtext>Pt</mml:mtext> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> at +0.85 V vs. RHE that is almost 50 times higher than that of commercial Pt/C.

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.

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 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 score0.011
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.298
Teacher spread0.264 · 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