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Record W2315117434 · doi:10.1021/jp408979h

Chemical Structure of Nitrogen-Doped Graphene with Single Platinum Atoms and Atomic Clusters as a Platform for the PEMFC Electrode

2014· article· en· W2315117434 on OpenAlexafffund
Samantha Stambula, Nicolas Gauquelin, Matthieu Bugnet, Sandeep Gorantla, Stuart Turner, Shuhui Sun, Jian Liu, Gaixia Zhang, Xueliang Sun, G. A. Botton

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2014
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern UniversityMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaBallard Power SystemsNatural Resources CanadaMcMaster University
KeywordsGrapheneMaterials scienceScanning transmission electron microscopyDopantTransmission electron microscopyCatalysisProton exchange membrane fuel cellAtomic layer depositionPlatinum nanoparticlesNanoparticleNanotechnologyPlatinumDopingChemical engineeringLayer (electronics)ChemistryOptoelectronics

Abstract

fetched live from OpenAlex

A platform for producing stabilized Pt atoms and clusters through the combination of an N-doped graphene support and atomic layer deposition (ALD) for the Pt catalysts was investigated using transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM). It was determined, using imaging and spectroscopy techniques, that a wide range of N-dopant types entered the graphene lattice through covalent bonds without largely damaging its structure. Additionally and most notably, Pt atoms and atomic clusters formed in the absence of nanoparticles. This work provides a new strategy for experimentally producing stable atomic and subnanometer cluster catalysts, which can greatly assist the proton exchange membrane fuel cell (PEMFC) development by producing the ultimate surface area to volume ratio catalyst.

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 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 score0.014
Threshold uncertainty score0.447

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 head0.199
Teacher spread0.194 · 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.

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

Citations143
Published2014
Admission routes2
Has abstractyes

Explore more

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