The Diels–Alder Reaction as a Mechanistic Probe for Vibrational Strong Coupling
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".