Transmission Coefficients for Chemical Reactions with Multiple States: Role of Quantum Decoherence
Bibliographic record
Abstract
Transition-state theory (TST) is a widely accepted paradigm for rationalizing the kinetics of chemical reactions involving one potential energy surface (PES). Multiple PES reaction rate constants can also be estimated within semiclassical approaches provided the hopping probability between the quantum states is taken into account when determining the transmission coefficient. In the Marcus theory of electron transfer, this hopping probability was historically calculated with models such as Landau-Zener theory. Although the hopping probability is intimately related to the question of the transition from the fully quantum to the semiclassical description, this issue is not adequately handled in physicochemical models commonly in use. In particular, quantum nuclear effects such as decoherence or dephasing are not present in the rate constant expressions. Retaining the convenient semiclassical picture, we include these effects through the introduction of a phenomenological quantum decoherence function. A simple modification to the usual TST rate constant expression is proposed: in addition to the electronic coupling, a characteristic decoherence time τ(dec) now also appears as a key parameter of the rate constant. This new parameter captures the idea that molecular systems, although intrinsically obeying quantum mechanical laws, behave semiclassically after a finite but nonzero amount of time (τ(dec)). This new degree of freedom allows a fresh look at the underlying physics of chemical reactions involving more than one quantum state. The ability of the proposed formula to describe the main physical lines of the phenomenon is confirmed by comparison with results obtained from density functional theory molecular dynamics simulations for a triplet to singlet transition within a copper dioxygen adduct relevant to the question of dioxygen activation by copper monooxygenases.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".