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Record W2027800088 · doi:10.1063/1.1793931

Effect of absolute laser phase on reaction paths in laser-induced chemical reactions

2004· article· en· W2027800088 on OpenAlexafffund
André D. Bandrauk, El-Wallid S. Sedik, Chérif F. Matta

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of TorontoUniversité de Sherbrooke
FundersKillam Trusts
KeywordsPolarizabilityDipoleChemistryAtomic physicsLaserMoment (physics)Ab initioTransition dipole momentReaction ratePhase (matter)Molecular physicsMoleculePhysicsOptics

Abstract

fetched live from OpenAlex

Potential surfaces, dipole moments, and polarizabilities are calculated by ab initio methods [unrestricted MP2(full)/6-311++G(2d,2p)] along the reaction paths of the F+CH4 and Cl+CH4 reaction systems. It is found that in general dipole moments and polarizabilities exhibit peaks near the transition state. In the case of X=F these peaks are on the products side and in the case of X=Cl they are on the reactants side indicating an early transition state in the case of fluorine and a late transition state in the case of chlorine. An analysis of the geometric changes along the reaction paths reveals a one-to-one correspondence between the peaks in the electric properties and peaks in the rate of change of certain internal geometric coordinates along the reaction path. Interaction with short infrared intense laser fields pulses leads to the possibility of interferences between the dipole and polarizability laser-molecule interactions as a function of laser phase. The larger dipole moment in the Cl+CH4 reaction can lead to the creation of deep wells (instead of energy barriers) and new strongly bound states in the transition state region. This suggests possible coherent control of the reaction path as a function of the absolute phase of the incident field, by significant modification of the potential surfaces along the reaction path and, in particular, in the transition state region.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.298
Teacher spread0.286 · 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 teacher head, 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

Citations74
Published2004
Admission routes2
Has abstractyes

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