Stochastic resonance interpretation of temperature-dependent F-center formation in NaCl
Bibliographic record
Abstract
"Experiments by Tanimura and Hess have revealed that the formation of F centers after exciton creation in NaCl appears complete within >6 ps, a time too short to be consistent with thermally-activated conversion from self-trapped excitons (STE) in equilibrium. Yet the yield of prompt F centers is temperature-dependent. Molecular dynamics simulations of the relaxation from self-trapped excitons to F centers in NaCl have been performed as a function of modeled temperature, and are found to duplicate the main features of the seemingly paradoxical experimental observation. Additional insight is gained from the MD simulations by being able to observe excitation of a long-lived local vibrational mode on the compacted anion row produced by the off-center STE. The MD results indicate that the defect formation rate increases with temperature from 10 K up to about 100 K, and decreases above about 200 K. This thermal "resonance" in the yield of prompt defect formation, along with the presence of a vibrational soliton forcing motion along the reaction coordinate, are interpreted as an example of stochastic resonance in defect formation. The same explanation may explain the dynamic interstitial phenomenon, i.e. observation that a freshly created H center has a lower thermal activation energy for transport than an equilibrated H center."
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".