Pressure Scanning Volumetry of Physically Aged Polymer Glasses, Fictive Pressure, and Memory Effect
Bibliographic record
Abstract
Physical aging of a glass decreases its volume, V, entropy, and enthalpy, H, toward the equilibrium state values. For glasses usually formed by cooling a melt, the effect is modeled in terms of non-exponential, nonlinear structural relaxation by using a plot of the heat capacity, C p = (d H /d T ) p, against T obtained from differential scanning calorimetry (DSC) cooling and heating scans. A melt becomes glass also on isothermal pressurizing and the glass formed becomes liquid on depressurizing, showing a hysteresis of the sigmoid-shape plot of −(d V /d p ) T against p, which resembles the thermal hysteresis observed in the C p against T plots. By analogy with DSC, it was named pressure scanning volumetry (PSV). Here, we use the known values of non-exponential and nonlinearity parameters β and x and volume of activation for structural relaxation time, Δ V *, of atactic poly(propylene) to investigate the effect of aging pressure, p age, of aging time, t age, and of the pressurizing rate on aging features in PSV scans. The scans show a post- p g → l feature on depressurizing before the −(d V /d p ) T overshoot peak appears. We provide quantitative plots (i) of the monotonic decrease of V and increase of fictive pressure, p f, with t age and (ii) of the memory (Kovacs) effect in V and p f of the polymer and (iii) provide generic plots of −(d V /d p ) T against p for different combinations of β, x, and Δ V *. The study is of academic significance because PSV scans show a change in the density fluctuation response. It is of technological significance in polymer-extrusion processing and it may stimulate the commercial development of computer-controlled, high-pressure equipment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".