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Record W1883576699 · doi:10.1139/cjc-2013-0334

Density functional theory studies on adsorption and decomposition mechanism of FOX-7 on Al<sub>13</sub> clusters

2013· article· en· W1883576699 on OpenAlexvenueno aff
Caichao Ye, Fengqi Zhao, Siyu Xu, Xue‐Hai Ju

Bibliographic record

VenueCanadian Journal of Chemistry · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersGovernment of Jiangsu Province
KeywordsChemistryAdsorptionDensity functional theoryDecompositionCluster (spacecraft)MoleculeActivation energyPhysical chemistryAtmospheric temperature rangeComputational chemistryAluminiumPotential energy surfaceCrystallographyChemical physicsThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

The adsorption and decomposition of the FOX-7 molecule on Al13 clusters were investigated by generalized gradient approximation of the density functional theory. The strong attractive forces between the FOX-7 molecule and aluminum atoms induce the N−O bond breaking of FOX-7. Subsequently, the dissociated oxygen atoms and radical fragment of FOX-7 oxidize the aluminum clusters. The largest adsorption energy is −1020.4 kJ/mol. We also investigated three adsorption reaction paths of the FOX-7 molecule on the Al13 clusters in the A configuration. The activation energy for the adsorption steps are 0.2, 11.4, and 10.2 kJ/mol, respectively, and Al13 is more active than the Al(111) surface and the Al13 cluster performs better in decreasing the adsorption barrier of FOX-7 on the aluminum surface as well. The rate constants of three adsorption paths increase as temperature increases over the temperature range 275–500 K.

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)0.000
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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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