Effect of pressure on thermal conductivity and pressure collapse of ice in a polymer-hydrogel and kinetic unfreezing at 1 GPa
Bibliographic record
Abstract
We report a study of aqueous solutions of poly(vinylalcohol) and its hydrogel by thermal conductivity, κ, and specific heat measurements. In particular, we investigate (i) the changes in the solution and the hydrogel at 0.1 MPa observed in the 350-90 K range and of the frozen hydrogel at 130 K observed in the range from 0.1 MPa to 1.3 GPa, and (ii) the nature of the pressure collapse of ice in the frozen hydrogel and kinetic unfreezing on heating of its high density water at 1 GPa. The water component of the polymer solution on cooling either first phase separates and then freezes to hexagonal ice or freezes without phase separation and the dispersed polymer chains freeze-concentrate in nanoscopic and microscopic regions of the grain boundaries and grain junctions of the ice crystals in the frozen state of water in the hydrogel. The change in κ with temperature at 1 bar is reversible with some hysteresis, but not reversible with pressure after compression to 0.8 GPa at 130 K. At high pressures the crystallized state collapses showing features of κ and specific heat characteristic of formation of high density amorphous solid water. The pressure of structural collapse is 0.08 GPa higher than that of ice at 130 K. The slowly formed collapsed state shows kinetic unfreezing or glass-liquid transition temperature at 140 K for a time scale of 1 s. Comparison with the change in the properties observed for ice shows that κ decreases when the polymer is added.
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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 | 0.001 |
| 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".