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Record W2313176923 · doi:10.1021/la202913b

Electro-oxidation of CO<sub>chem</sub> on Pt Nanosurfaces: Solution of the Peak Multiplicity Puzzle

2011· article· en· W2313176923 on OpenAlexaff
Patrick Urchaga, Stéve Baranton, Christophe Coutanceau, Gregory Jerkiewicz

Bibliographic record

VenueLangmuir · 2011
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsQueen's University
Fundersnot available
KeywordsStripping (fiber)NanoparticleChemistryMultiplicity (mathematics)OctahedronElectrodeOxidative phosphorylationCrystallographyMaterials scienceNanotechnologyPhysical chemistryCrystal structure

Abstract

fetched live from OpenAlex

An understanding of the oxidation of chemisorbed CO (CO(chem)) on Pt nanoparticle surfaces is of major importance to fuel cell technology. Here, we report on the relation between Pt nanoparticle surface structure and CO(chem) oxidative stripping behavior. Oxidative stripping voltammograms are obtained for CO(chem) preadsorbed on cubic, octahedral, and cuboctahedral Pt nanoparticles that possess preferentially oriented and atomically flat domains. They are compared to those obtained for etched and thermally treated Pt(poly) electrodes that possess atomically flat, ordered surface domains separated by grain boundaries as well as those obtained for spherical Pt nanoparticles. A detailed analysis of the results reveals for the first time the presence of up to four voltammetric features in CO(chem) oxidative stripping transients, a prepeak and three peaks, that are assigned to the presence of surface domains that are either preferentially oriented or disordered. The interpretation reported in this article allows one to explain all features within the voltammograms for CO(chem) oxidative stripping unambiguously.

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 score0.489

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 head0.017
GPT teacher head0.211
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

Citations137
Published2011
Admission routes1
Has abstractyes

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