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Record W2081728940 · doi:10.1039/c2cp41286a

CO oxidation on Pt nanoclusters, size and coverage effects: a density functional theory study

2012· article· en· W2081728940 on OpenAlexaff
Sergey Dobrin

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2012
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsYork University
FundersDanmarks Tekniske Universitet
KeywordsNanoclustersCluster (spacecraft)Density functional theoryCluster sizeAtom (system on chip)PlatinumChemistryCrystallographyChemical physicsCrystal (programming language)Single crystalMaterials scienceAtomic physicsNanotechnologyComputational chemistryElectronic structurePhysicsCatalysis

Abstract

fetched live from OpenAlex

CO oxidation on Pt nanoclusters of approximately 1 nm in size was studied using density functional theory (DFT). Reaction barriers on various sites of a cuboctahedral 55-atom cluster and of several two-layer plane clusters representing (111) and (100) facets of the 147-atom cluster have been calculated at various coverage. The effect of atomic structure of various clusters was discussed. It was concluded that the 147-atom cuboctahedral cluster reveals properties of the Pt single crystal surfaces, while a 55-atom cluster cannot be fully described in terms of Pt single crystal surfaces. It was found that CO oxidation may occur faster at higher coverage and that for cluster sizes up to a few nanometers in size, larger platinum clusters can be more efficient in CO oxidation than the smaller clusters. The size effect was found to depend upon coverage.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 designSimulation or modeling
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

Citations55
Published2012
Admission routes1
Has abstractyes

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