Effect of Temperature on Foaming Behaviors of Homo- and Co-polymer Polypropylene/Polydimethylsiloxane Blends with CO2
Bibliographic record
Abstract
Poly(dimethylsiloxane) (PDMS) was blended with two different types of polypropylene (PP). The blends were subsequently batch-foamed with supercritical CO 2 at a series of temperatures that varied by a narrow increment of 2°C to investigate the effect of the foaming temperature on foaming. In the case of the random copolymer PP, it was found that the cell density of the blends containing PDMS increased significantly and good cell structures could be obtained across a wide temperature spectrum. PDMS typically generated high CO 2 concentration and low surface tension, which positively impacted the cell nucleation. In the case of linear homopolymer PP, the addition of PDMS did not result in any pronounced improvement to cell morphology; however, at very low temperatures, much lower than the melting point, a few very small cells appeared. In both experiments, the addition of maleic anhydride grafted PP (PP-g-MAH) as a compatibilizer promoted the dispersion of PDMS and yielded a better cell morphology within a specific temperature range. Moreover, the presence of a compatibilizer enhanced the melt strength, which in turn served to broaden the processing window.
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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) | 0.000 | 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".