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Record W2303027028 · doi:10.1149/1.3635700

Pt<sub>7</sub>Sn<sub>3</sub> Catalysts for Ethanol Electro-Oxidation: Correlation between Surface Structure and Catalytic Activity

2011· article· en· W2303027028 on OpenAlexaff
Elena A. Baranova, Kateryna Artyushkova, Barr Halevi, Tariq Amir, Ulises Martinez, Plamen Atanassov

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsX-ray photoelectron spectroscopyCatalysisMetalChemistryAnalytical Chemistry (journal)Particle sizeInorganic chemistryMaterials scienceChemical engineeringPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

X-ray photoelectron spectroscopy has been chosen to study the surface chemistry of carbon-supported PtSn catalysts of 70:30 at.% composition. Correlation of XPS structural information with catalytic performance for ethanol electro-oxidation in acidic solution, average particle size and structural characteristics is accomplished by application of multivariate statistical methods of data analysis (MVA). From structure to property correlations it was found that the best performing electrocatalysts do not have largest absolute amounts of Pt and Sn on the surface, whereas samples with largest amount of total Pt and Sn have the worst catalytic activity. It is shown that relative distribution of types of Pt and Sn is more important than the absolute amounts. Samples showing the highest current densities have small amounts of both metals, but have largest relative amount of both metallic Pt and metallic Sn. The same best performing samples have fewest amounts of all types of oxides, i.e. PtO, PtO2 and SnOx.

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 categoriesMeta-epidemiology (narrow)
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 score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.214
Teacher spread0.200 · 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.

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

Citations5
Published2011
Admission routes1
Has abstractyes

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