Determination of Solubilities of CO<sub>2</sub> in Linear and Branched Polypropylene Using a Magnetic Suspension Balance and a <i>PVT</i> Apparatus
Bibliographic record
Abstract
Using a PVT apparatus for high pressure and temperature combined with a magnetic suspension balance, the solubility of carbon dioxide in linear and branched polypropylene (PP) was measured at temperatures from (453 to 493) K and at pressures of up to 31 MPa. The solubility of CO 2 in both molten polymers increased linearly with pressure and decreased with temperature. However, above 20 MPa, the solubility−pressure relationship was no longer linear. This might be due to a significant hydrostatic effect on the swelling of the polymer that results from gas absorption above 20 MPa, so that swelling is no longer linearly related to pressure. At a high pressure, swelling significantly affects solubility, which is then no longer linearly related to pressure. It was noted that linear PP absorbs more gas than branched PP, due to the branched PP’s chain entanglement. The solubility of CO 2 in the PP melts was compared with semiempirical data (determined by empirically measuring gas uptake and theoretically predicting swelling) and theoretical values calculated from the Simha−Somcynsky (SS) and Sanchez−Lacombe (SL) equations of state (EOSs). The Simha−Somcynsky equation of state (SS-EOS) was observed to have a better prediction capacity of the swelling effect and to thus provide better solubility predictions for both semiempirical and theoretical cases than the Sanchez−Lacombe equation of state (SL-EOS).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".