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Record W1969888621 · doi:10.1139/cjc-2014-0496

Vibrational excitation influence on the H + BrO → HBr + O reaction: a quasi-classical trajectory investigation

2015· article· en· W1969888621 on OpenAlexvenueno aff
Yingying Zhang, Ying Shi, Ting‐Xian Xie, Zerui Li, Zhan Hu, Mingxing Jin

Bibliographic record

VenueCanadian Journal of Chemistry · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryExcitationAtomic physicsScalar (mathematics)Reaction rate constantPotential energy surfaceAb initioPolarization (electrochemistry)Potential energyPhysical chemistryPhysicsQuantum mechanicsKinetics

Abstract

fetched live from OpenAlex

Quasi-classical trajectory calculations are employed to investigate the vibrational excitation effect on the scalar and vector properties of the H + BrO → HBr + O reaction using a X1A′ state ab initio potential energy surface (J. Chem. Phys. 2000, 113, 4598). The reaction probability, cross section, and rate constant are carried out with the effect of the collision energy (Ecol = 0.1–6 kcal/mol) and vibrational levels (v = 0–3). A significant vibrational dependency has been observed in the reaction probability and cross section at a relatively low collision energy area and has also been found in a low-temperature (T < 150 K) region of the rate constant. In addition, two product angular distributions, P(θr) and P(ϕr), and two generalized polarization-dependent differential cross sections, PDDCS00 and PDDCS20, are calculated as well. All of these scalar and vector properties have shown sensitive behaviors to the vibrational levels.

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)0.000
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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