MétaCan
Menu
Back to cohort
Record W2044750078 · doi:10.1021/jp063856k

Kinetic Modeling of CO<sub>a</sub><sub>d</sub> Monolayer Oxidation on Carbon-Supported Platinum Nanoparticles

2006· article· en· W2044750078 on OpenAlexaff
Bernhard Andreaus, Frédéric Maillard, Joanna Kocylo, Elena R. Savinova, Michael Eikerling

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2006
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNucleationNanoparticleKinetic Monte CarloKinetic energyMonolayerPlatinumMaterials scienceReaction rate constantChemistryChemical physicsPhysical chemistryMonte Carlo methodNanotechnologyKineticsCatalysisPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

We present a theoretical study of CO(ad) electrooxidation on Pt nanoparticles. Effects of size and surface texture of nanoparticles on the interplay of relevant kinetic processes are investigated. Thereby, strong impacts of particle size on electrocatalytic activities, observed in experiments, are rationalized. Our theoretical approach employs the active site concept to account for the heterogeneous surface of nanoparticles. It, moreover, incorporates finite rates of surface mobility of adsorbed CO. As demonstrated, the model generalizes established mean field or nucleation and growth models. We find very good agreement of our model with chronoamperometric current transients at various particle sizes and electrode potentials (Maillard, F.; Savinova, E. R.; Stimming, U. J. Electroanal. Chem., in press, doi:10.1016/j.jelechem.2006.02.024). The full interplay of on-site reactivity at active sites and low surface mobility of CO(ad) unfolds on the smallest nanoparticles ( approximately 2 nm). In this case, the solution of the model requires kinetic Monte Carlo simulations specifically developed for this problem. For larger nanoparticles (>4 nm) the surface mobility of CO(ad) is high compared to the reaction rate constants, and the kinetic equations can be solved in the limiting case of infinite surface mobility. The analysis provides an insight into the prevailing reaction mechanisms and allows for the estimation of relevant kinetic parameters.

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 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 score0.075
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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.

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

Citations73
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicElectrocatalysts for Energy ConversionFrench-language works237,207