Kinetic-freezing and unfreezing of local-region fluctuations in a glass structure observed by heat capacity hysteresis
Bibliographic record
Abstract
Fluctuations confined to local regions in the structure of a glass are observed as the Johari-Goldstein (JG) relaxation. Properties of these regions and their atomic configuration are currently studied by relaxation techniques, by electron microscopy, and by high-energy X-ray scattering and extended x-ray absorption fine structure methods. One expects that these fluctuations (i) would kinetically freeze on cooling a glass, and the temperature coefficient of its enthalpy, dH/dT, would consequently show a gradual decrease with decrease in T, (ii) would kinetically unfreeze on heating the glass toward the glass-liquid transition temperature, Tg, and dH/dT would gradually increase, and (iii) there would be a thermal hysteresis indicating the time and temperature dependence of the enthalpy. Since no such features have been found, thermodynamic consequences of these fluctuations are debated. After searching for these features in glasses of different types, we found it in one of the most stable metal alloy glasses of composition Pd40Ni10Cu30P20. On cooling from its Tg, dH/dT decreased along a broad sigmoid-shape path as local-region fluctuations kinetically froze. On heating thereafter, dH/dT increased along a similar path as these fluctuations unfroze, and there is hysteresis in the cooling and heating paths, similar to that observed in the Tg-endotherm range. After eliminating other interpretations, we conclude that local-region fluctuations seen as the JG relaxation in the non-equilibrium state of a glass contribute to its entropy, and we suggest conditions under which such fluctuations may be observed.
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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 | 0.001 | 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".