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Record W2898258431 · doi:10.1021/acscatal.8b01760

Catalytic Consequences of Reactive Intermediates during CO Oxidation on Ag Clusters

2018· article· en· W2898258431 on OpenAlexafffund
Petar T. Lachkov, Ya-Huei Cathy Chin

Bibliographic record

VenueACS Catalysis · 2018
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoCanada Foundation for Innovation
KeywordsChemistryCatalysisReaction rate constantCluster (spacecraft)KineticsKinetic energyCarbon monoxideStoichiometryAnalytical Chemistry (journal)Physical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Kinetic measurements, microkinetic modeling, and CO and O2 uptake experiments lead to a proposed mechanism for CO oxidation on dispersed Ag cluster surfaces. CO turnovers occur via kinetically relevant reactions between O2* and CO* on Ag cluster surfaces nearly saturated with O* and CO*. The operating pressure ratio of O2 to the square of CO, [O2]-to-[CO]2, dictates the relative O* and CO* coverages and in turn the rate coefficients. Low [O2]-to-[CO]2 ratios lead to Ag cluster surfaces saturated with CO*, during which the first-order rate coefficients (rCO[CO]−1) increase linearly with the pressure ratio. As the [O2]-to-[CO]2 ratio increases, the CO* coverages decrease and O* coverages concomitantly increase, and the rate coefficients become independent of the [O2]-to-[CO]2 ratio. CO* binds to Ag clusters more strongly than O*, and as a result, CO* coverages decrease and O* coverages increase as the reaction temperature rises when comparing at a constant [O2]-to-[CO]2 ratio. The rate coefficients for CO oxidation on CO* covered Ag clusters initially increase with increasing Ag cluster diameter to ∼5 nm, but decrease with a further increase in Ag diameter beyond 5 nm. The former trend reflects more weakly bound and reactive O2* and CO*, and the latter likely reflects the depletion of O2* molecules.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.002
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

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