Effect of Unexpected CO<sub>2</sub>’s Phase Transition on the High-Pressure Differential Scanning Calorimetry Performance of Various Polymers
Bibliographic record
Abstract
We used a high-pressure differential scanning calorimeter (HP-DSC) to study polymer plasticization by compressed gases at pressures of up to 30 MPa for polylactide (PLA), polycarbonate (PC), isotactic polypropylene (iPP), and polystyrene (PS). The pressure reached values twice as high as the previously published data. We found that the polymer/carbon dioxide (CO 2 ) system’s heating curves have an unidentified endothermic peak above 5 MPa, which turns out to be from CO 2 ’s phase transition. The HP-DSC could accurately determine the depression of the glass transition temperature ( T g ), crystallization temperature ( T c ), and melting temperature ( T m ) of various polymers at low pressures by simply starting at a higher temperature to avoid CO 2 ’s phase transition; however, the increased plasticization effect of the dissolved CO 2 lowered the T g to the level of overlapping with CO 2 ’s phase transition phenomena at elevated pressures, and therefore, the depressed T g could not be measured above 6 MPa for PLA, PC, or PS. On the other hand, the T c of iPP decreased with an increase in pressure, whereas T m values of PLA and iPP decreased slightly with an increase in pressure and then remained almost unchanged above a certain pressure, which may indicate an increased hydrostatic pressure effect at elevated pressures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".