The temperature and polymerization effects on the relaxation time and conductivity, and the evolution of the localized motions
Bibliographic record
Abstract
To examine the manner in which molecular dynamics of a polymerizing liquid (stoichiometric amounts of 4,4′-diaminodicyclohexylamine and diglycidyl ether of bisphenol-A) evolves during thermal cycling from its (molecular) vitreous state to its fully polymerized vitreous state, calorimetry, and dielectric spectrometry were performed simultaneously in real time. The half-width of the relaxation spectrum of the liquid was relatively narrow and became narrower on heating. This was followed by an increase in the characteristic relaxation time and the spectrum became broader as polymerization occurred and reached completion. The dc conductivity initially increased and then decreased. The faster dynamics of the Johari–Goldstein relaxation in the fully polymerized state evolved as polymerization reached completion and the temperature increased. The dielectric polarization associated with this relaxation had a broad spectrum, whose half-width increased with decrease in the temperature. Its relaxation rate followed the Arrhenius equation with an activation energy of 63.4 kJ/mol. The temperature dependence of the faster relaxation did not change with the change in the overall configurational entropy of the liquid, a feature that substantiates the dynamic heterogeneity theories for the structure of the liquid and for the origin of the relaxation.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".