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Record W4412522797 · doi:10.1021/acs.jpclett.5c01196

Revealing Transition State Signatures in Collisional Vibrational Quenching Aided by Conical Intersections

2025· article· en· W4412522797 on OpenAlexaff
Hanzi Zhang, Qixin Chen, Feng An, Hua Guo, Daiqian Xie, Weigao Xu, Xixi Hu, Shanyu Han

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsMinistry of Education and Child Care
FundersNanjing UniversityNational Natural Science Foundation of China
KeywordsDiabaticConical surfaceScatteringAb initioPotential energyQuenching (fluorescence)Conical intersectionAtomic physicsVibronic couplingChemistryMolecular physicsCoupling (piping)Transition statePhysicsExcited stateMaterials scienceQuantum mechanics

Abstract

fetched live from OpenAlex

We dissect the dynamics of vibrational quenching of HBr by collisions with atomic iodine, which are affected by conical intersections in the strongly interacting regions. Trajectory surface hopping calculations using a newly developed ab initio-based diabatic potential energy matrix reveal that the vibrational inelasticity stems largely from a "frustrated reaction" mechanism, in which the trajectories access the vicinity of a reactive transition state where intermodal coupling is strong. This is aided by nonadiabatic transitions near conical intersections. In addition, the vibration-rotation energy transfer leads to a forward scattering bias, following a hard collision glory scattering mechanism, facilitated by a delicate counterbalance between attractive and repulsive forces.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.246
Teacher spread0.242 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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