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Record W1980245438 · doi:10.1021/jp003827o

Above-Threshold Effects in the Photodissociation and Photoionization of Iodobenzene

2001· article· en· W1980245438 on OpenAlexaff
Sujatha Unny, Yan Du, Langchi Zhu, Kaspars Truhins, Robert J. Gordon, A. Sugita, Masahiro Kawasaki, Yutaka Matsumi, Ralph Delmdahl, David H. Parker, Attila Bérces

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsAutoionizationAtomic physicsPhotoionizationRydberg formulaIodobenzeneExcited statePhotodissociationDissociation (chemistry)IonizationIonExcitationRydberg stateChemistryPhysicsPhotochemistry

Abstract

fetched live from OpenAlex

The method of velocity map imaging is used to investigate the photoinduced dynamics of iodobenzene in weak laser fields as well as in fields of sufficient intensity to produce multiphoton excitation without dressing the potential energy surfaces. The speed and angular distributions of the recoiling iodine atoms observed with weak fields at 266 and 304 nm are in good agreement with previous studies, showing evidence of dissociation via n,σ* and π,π* states. Density functional theory calculations are used to determine the energies of the excited states. Ion and electron images produced with intense visible radiation (532−609 nm, 3 × 10 10 to 5 × 10 12 W/cm 2 ) show both two-photon threshold dissociation and higher order (four- to seven-photon) ionization processes. A unique characteristic of the I + images obtained with intense visible radiation is a continuous, hourglass-shaped feature peaked at zero kinetic energy, displaying highly nonstatistical speed and angular distributions. A mechanism that is consistent with all of the observations is dissociative autoionization of a superexcited repulsive Rydberg state.

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 score0.049
Threshold uncertainty score0.128

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 integrity0.0000.000
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 head0.005
GPT teacher head0.249
Teacher spread0.244 · 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

Citations38
Published2001
Admission routes1
Has abstractyes

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