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Record W1806930973 · doi:10.1139/v11-059

Quasi-classical trajectory study of the O(<sup>1</sup>D) + HF reaction dynamics on 1<sup>1</sup>A′ potential energy surface

2011· article· en· W1806930973 on OpenAlexvenueno aff
Juan Zhao

Bibliographic record

VenueCanadian Journal of Chemistry · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPotential energy surfaceReaction dynamicsSinglet stateExcitationExcitation functionReaction mechanismAtomic physicsScalar (mathematics)ReagentWave functionPotential energyComputational chemistryNuclear reactionPhysical chemistryPhysicsQuantum mechanicsExcited stateMolecule

Abstract

fetched live from OpenAlex

The quasi-classical trajectory (QCT) calculations for the title reaction were carried out using the recently developed, accurate potential energy surface (PES) of the [Formula: see text] singlet state of the OHF system The integral cross section and the product rotational alignment factor [Formula: see text] were calculated as a function of collision energy. In addition, I discovered the effect of isotopic substitution on stereodynamics for the title reaction, and the influence of the rotation excitation of the reagent on stereodynamics is also presented. Both the scalar and vector properties of the reaction O(1D) + HF → OH + F(2P) are studied in this paper. It was found that the reaction is mainly controlled by an indirect reaction mechanism, and that the deep noncollinear insertion HOF well has a great impact on the dynamics of the reaction. The conclusions drawn in this paper will draw from references to similar reactions, and provide a theoretical foundation for related experiments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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

Citations11
Published2011
Admission routes1
Has abstractyes

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