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Record W1981770185 · doi:10.1139/v09-016

Effect of surface heterogeneity steps-terraces in a mean field model for the catalytic CO-NO reaction

2009· article· en· W1981770185 on OpenAlexvenueno aff
Joaquı́n Cortés, Eliana Valencia

Bibliographic record

VenueCanadian Journal of Chemistry · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersFondo Nacional de Desarrollo Científico y Tecnológico
KeywordsChemistryCatalysisKinetic energyActivation energyThermodynamicsPhysical chemistryReaction mechanismSign (mathematics)Reaction rate constantChemical physicsKineticsOrganic chemistryClassical mechanics

Abstract

fetched live from OpenAlex

Based on a model proposed by Olsson et al. (Surf. Sci. 2003, 529, 338), a study is made through a mean field scheme of the effect of steps-terraces superficial heterogeneity, whose energy differences have been determined recently by means of density functional theory (DFT), in the catalytic reduction reaction of NO by CO over palladium. Several aspects are seen, such as the relation between the activities produced in both sectors of the surface as a function of temperature and the energy difference between them, the activity and coverage versus the temperature and the gas phase concentration curves, and the effect on these variables of the activation energy values on the steps of some stages of the kinetic mechanism. The system shows a reaction order with respect to CO and NO that changes sign between low and high temperatures, from negative to positive in the case of CO and the opposite for NO.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
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 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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venueCanadian Journal of ChemistrySame topicCatalytic Processes in Materials ScienceFrench-language works237,207