Prediction of reaction barriers and force-induced instabilities under mechanochemical conditions with an approximate model: A case study of the ring opening of 1,3-cyclohexadiene
Bibliographic record
Abstract
Mechanochemistry, the use of mechanical stresses to activate chemical reactions, has emerged as a topic of significant interest. The present study examines the use of an approximate model for the prediction of reaction barriers under mechanochemical conditions using the ring opening of 1,3-cyclohexadiene along conrotatory and disrotatory directions as a specific test case. To do this, reaction barriers are evaluated using quantum chemical methods with an external force applied between various pairs of atoms. The results show that the consequent effects on the barrier exhibit a significant dependence on the locations of the atoms used to apply the external force, and in some cases, force-induced instabilities occur that alter the fundamental nature of the reaction pathway. The ability of an approximate model based on a second-order expansion of the force-modified potential energy with respect to nuclear coordinates to reproduce this behavior is then assessed. Good agreement between the results obtained through the quantum chemical calculations and approximate model is attained when force-induced instabilities do not occur. In addition, a strategy for predicting when such instabilities occur is presented and found to yield results that are in qualitative agreement with the quantum chemical calculations. Finally, the response of the system to the external force is interpreted in terms of the parameters entering the model, which correspond to interatomic distances and stiffnesses, and possibly sheds lights on ways to design molecules that exhibit a desired chemical response to mechanochemical conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".