Collision time of a triatomic chemical reaction A + BC
Bibliographic record
Abstract
The collision time is an important quantity of an elementary chemical reaction and describes the speed of the collision process in a collision reaction. In this study, we present a generalized method to calculate the collision time of a triatomic reaction in which the collision time is defined by the sum of the incoming time, the intermediate complex time, and the outgoing time. Two variables including the total distance Rtotal and Ravg, the average value of Rtotal over time, are used to compute the three components of the collision time. We compute three triatomic reactions including Ca + HCl → CaCl + H, O + HCl → OH + Cl/OCl + H, and O + HF → OH + F at different collision energies and initial diatomic vibrational levels using the quasi-classical trajectory method to confirm that the method could be reliable and reasonable. The time evolutions of Rtotal could efficiently classify the direct and indirect reactive mechanisms and reveal a distinct discrepancy of the two mechanisms. As the collision energy and initial diatomic vibrational level increase, the percentage of direct reaction trajectories increases. At the same time, the average and maximal values of collision time decrease. Comparing the maximal collision time and the reactive probability distributions of the products, it could be found that most reactive trajectories’ collision time is less than 2 ps. Moreover, the present calculations indicate that the method could be applicable to estimate the lifetime of the intermediate complex for the reaction systems with deep potential wells and the collision time of the reactions with a direct abstraction mechanism.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".