Stereodynamic insight into the thermal history effects on poly(vinyl chloride) calorimetric sub-glass and glass transitions as a fragile glass model
Bibliographic record
Abstract
The dynamic thermal history impact of poly(vinyl chloride) (PVC) has been explored for a wide range of pre-cooling rates, from 1 to 30 °C min-1. A first macroscopic insight into the dynamic thermal history influence has been highlighted through a decrease in the apparent activation energy (Eapp) in the first stage of the glass transition. The overall glass transition Eapp surface was successfully modeled in a polynomial fashion regarding the pre-cooling range. Raman scattering was used to associate the Eapp variations along the glass transition conversion with the stereochemistry evolution during the polymeric relaxation. Herein, the selection of atactic PVC as the polymer model permits us to monitor the glassy polymer segment stereodynamics during the heating ramp through the C-Cl stretching. The intermolecular H-Cl dipole interactions, as well as intramolecular conformational reorganizations among syndiotactic, isotactic and heterotactic polymer sequences, have been associated with non-cooperative and cooperative motions, i.e. the β- and α-process, respectively. The fruitful comparison of the two extreme values of the pre-cooling rates permits us to propose a thermokinetic scenario that explains the occurrence, intensity, and inter-dependence of β- and α-processes in the glassy state and during the glass transition. This scenario could potentially be generalized to all the other polymeric glass-formers.
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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".