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Record W2280018472 · doi:10.1139/cjc-2015-0278

Oxygen adsorption and diffusion on an Al(111) surface and subsurface: a theoretical study

2016· article· en· W2280018472 on OpenAlexvenueno aff
Su‐Qin Zhou, Yangyang Wu, Siyu Xu, Fengqi Zhao, Xue‐Hai Ju

Bibliographic record

VenueCanadian Journal of Chemistry · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
Fundersnot available
KeywordsAdsorptionChemistryPhysisorptionChemisorptionOxygenDissociation (chemistry)MoleculeMonolayerDiffusionAtom (system on chip)Surface diffusionDensity functional theoryPhysical chemistryOxygen atomChemical physicsInorganic chemistryComputational chemistryThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

The generalized gradient approximation of the density functional theory was used to investigate the adsorption and dissociation of the O2 molecule on an Al(111) surface and the subsequent diffusion of an oxygen atom into the subsurface with different oxygen coverages. The total adsorption energies of oxygen atoms on the Al(111) surface increase as the number of adsorbed oxygen atoms increases, while the adsorption heats per oxygen atom decrease firstly and then increase. The adsorption heats for O2 physisorption on the Al(111) surface would increase as the oxidization degree of Al(111) surface increased. As the oxidization degree of Al(111) surface increases, the adsorption heats for O2 chemisorption decrease firstly and then increase, and the O2 molecule would not dissociate when the oxidization degree was up to 1.0 monolayer. In general, the energy barriers for both the interlayer and intralayer diffusions of the oxygen atom on the Al(111) surface would become larger as the number of initial adsorbed oxygen atoms on the Al(111) surface increased due to an increasing repulsion force.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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 designTheoretical or conceptual
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

Citations9
Published2016
Admission routes1
Has abstractyes

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