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Record W2132781126 · doi:10.1002/qua.20436

Potential energy surfaces in Coulomb explosion of polyatomic molecules: Benzene and cyclohexane trications and acetylene dication

2005· article· en· W2132781126 on OpenAlexaff
Alexander M. Mebel, T. S. Zyubina, Yu. A. Dyakov, André D. Bandrauk, S. H. Lin

Bibliographic record

VenueInternational Journal of Quantum Chemistry · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDicationCoulomb explosionChemistryIsomerizationAb initioDissociation (chemistry)CyclohexaneAcetyleneComputational chemistryMoleculePotential energy surfacePotential energyAtomic physicsPhysical chemistryIonIonizationPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract We report density functional and ab initio calculations of potential energy surfaces (PES) for benzene and cyclohexane trications relevant to the Coulomb explosion mechanisms of C6H6 and C6H12. Numerous isomerization and dissociation mechanisms on these PES have been considered, and the products most favorable thermodynamically and kinetically have been predicted. We also demonstrate applications of RRKM theory to the calculation of product branching ratios in decomposition of multiply charged cations. Significant common features of PES related to Coulomb explosion experiments on hydrocarbon molecules have been described. Calculations along minimal energy reaction paths for some representative isomerization and dissociation channels have been carried out in the presence of strong external electric field for C6H and C2H and the influence of the field on molecular orientation and PES have been analyzed. The results show that proton mobility in nonaromatic hydrocarbon cations is high due to nearly zero barriers for the H+ migrations. © 2005 Wiley Periodicals, Inc. Int J Quantum Chem, 2005

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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.250
Teacher spread0.245 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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