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Record W2264069510 · doi:10.1021/acs.jpcc.5b07206

Second Order Dependence on the Surface Fraction of Pt in Pt—Ru<sub>adatom</sub> of the Oxidation of 2-PrOH in Base

2015· article· en· W2264069510 on OpenAlexafffund
Matthew Markiewicz, Steven H. Bergens

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2015
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsDehydrogenationCatalysisRutheniumChemistryPlatinumElectrolyteKinetic energyStoichiometryKinetic isotope effectBase (topology)Physical chemistryInorganic chemistryAnalytical Chemistry (journal)ElectrodeDeuteriumOrganic chemistryAtomic physics

Abstract

fetched live from OpenAlex

The electrooxidation of 2-PrOH in alkaline electrolyte is studied over a series of Pt-Ru adatom catalysts with controlled surface compositions as a function of potential and temperature. Multivariable analysis is used to determine both kinetic and thermodynamic parameters of interest. PtRu surfaces are found to be more active at low potentials than either Pt or Ru alone. At moderate overpotentials, Pt is the most active catalyst due to a surface blocking effect by Ru. A clear second order dependence on the surface fraction of Pt is determined, and a kinetic isotope effect suggest that both C—H(D) and O—H(D) bonds are broken before or during the rate-determining step for the electro-dehydrogenation of 2-propanol to acetone. Possible mechanisms that account for these observations are discussed.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations2
Published2015
Admission routes2
Has abstractyes

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