The mechanism of the Baeyer–Villiger rearrangement: quantum chemistry and TST study supported by experimental kinetic data
Bibliographic record
Abstract
The mechanism of the Baeyer-Villiger rearrangement is modelled for the reaction of propanone with trifluoroperacetic acid, catalyzed by trifluoroacetic acid in dichloromethane, using three DFT methods (B3LYP, BH&HLYP and MPWB1K) and MP2. These results are refined and used to calculate the overall reaction rate coefficient using conventional Transition State Theory. The excellent agreement between the calculated (1.00 x 10(-3) L mol(-1) s(-1)) and the experimental (1.8 x 10(-3) L mol(-1) s(-1)) rate coefficients at the MPWB1K level strongly supports the mechanism recently proposed by our group. This DFT method is then used to study the mechanism of a larger system: cyclohexanone + trifluoroperacetic acid, for which a very good agreement between the calculated and the experimental rate coefficients is also found (1.37 and 0.32 L mol(-1) s(-1), respectively). The modelled mechanism is not ionic but neutral, and consists of two concerted steps. The first one is strongly catalyzed while the second one, the migration step, seems not to be catalyzed for the systems under study. The results of this work could be of interest for understanding other reactions in non-polar solvents for which ionic mechanisms have been assumed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".