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Record W4411995355 · doi:10.1002/ange.202509391

The Diels–Alder Reaction as a Mechanistic Probe for Vibrational Strong Coupling

2025· article· en· W4411995355 on OpenAlexaff
Cyprien Muller, Maciej Piejko, Sinan Bascil, Joseph Moran

Bibliographic record

VenueAngewandte Chemie · 2025
Typearticle
Languageen
FieldChemistry
TopicMolecular Spectroscopy and Structure
Canadian institutionsUniversity of Ottawa
FundersAgence Nationale de la Recherche
KeywordsDiels–Alder reactionCoupling (piping)Computational chemistryChemistryChemical physicsPhotochemistryMaterials scienceOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract Vibrational Strong Coupling (VSC) has recently been reported to alter reaction kinetics. Hypotheses on how it does this have been proposed, but open questions remain regarding the importance of the polarity of the reaction mechanism and of intramolecular vibrational redistribution (IVR), among other factors. We propose the Diels–Alder (DA) reaction as a probe to study chemistry under VSC, owing to the high diversity of its reaction partners. Herein, fixed‐width cavities and UV–vis spectroscopy were used to determine the rate constants for the reactions of the diene 1,3‐diphenylisobenzofuran (DPIBF) with various dienophiles under different coupling conditions. We investigated the effect of coupling six different solvents and of cooperative coupling of the dienophile through the solvent. Secondly, as the DA reaction can be catalyzed by hydrogen bonding, we investigated how the reaction was influenced by coupling alcohol solvents. Finally, we explored the direct coupling of vibrational modes of the dienophiles, including the stretching mode of the reactive C═C bond. In all cases, no substantial changes to the reaction rate constants were observed among the diverse coupling scenarios explored. This work initiates the use of the DA reaction as a mechanistic platform to understand how VSC changes chemistry and invites further experimental and theoretical studies.

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: none
Teacher disagreement score0.772
Threshold uncertainty score0.399

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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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