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Record W1974011271 · doi:10.1002/jrs.1449

The excited‐state geometry of 1‐hydroxy‐2‐ acetonaphthone: a resonance Raman and quantum chemical study

2006· article· en· W1974011271 on OpenAlexaff
Adriana Szeghalmi, Volker Engel, Marek Z. Zgierski, Jürgen Popp, Michael Schmitt

Bibliographic record

VenueJournal of Raman Spectroscopy · 2006
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsRaman spectroscopyIntramolecular forceExcited stateResonance Raman spectroscopyChemistryResonance (particle physics)ExcitationMolecular vibrationMolecular physicsObservableAtomic physicsComputational chemistryNuclear magnetic resonancePhysicsStereochemistryOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract 1‐Hydroxy‐2‐acetonaphthone (HAN), an intramolecular proton transfer system, was investigated in the present study by means of quantum chemical calculations and resonance Raman spectroscopy. To determine the Franck–Condon parameters, a time‐dependent approach for the analysis of the resonance Raman spectra was applied. About 18 vibrational modes were found to be involved in the initial dynamics of HAN upon photo excitation. Moreover, the excited‐state geometry of HAN was optimized at the CASSCF level of theory and the displacement parameters were determined. A very good agreement between the theoretical and experimentally derived parameters was obtained. The vibrations with the highest displacements correspond to stretching and in‐plane deformation modes of the naphthalene ring and the conjugated carbonyl group, while the OH stretching mode exhibits no observable enhancement. Hence, a general molecular rearrangement takes place upon photo excitation, where the intramolecular oxygen–oxygen distance reduces corresponding to a redistribution of the electron density. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.001
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 score0.007
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.241
Teacher spread0.236 · 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

Citations21
Published2006
Admission routes1
Has abstractyes

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