Rotational foam molding of polypropylene with control of melt strength
Bibliographic record
Abstract
Abstract Polypropylene (PP) has not been used extensively in rotational foam molding because it has been traditionally considered as nonfavorable for foaming applications because of its relatively weak melt strength and melt elasticity at elevated temperatures. However, because of the unique end‐use properties of PP, PP foams have recently grown in importance. An experimental study was conducted to identify feasible processing strategies for producing PP foams with satisfactory morphologies in dry‐blending‐based rotational foam molding. The obtained results revealed that cell coalescence plays a key role in the production of PP foams in rotational foam molding. If it is efficiently suppressed, the cell morphology of the PP foams improves dramatically. To suppress cell coalescence, it would be necessary to preserve the melt strength of PP during processing. One way of doing this is maintaining the temperature of the PP melt as low as possible. This can be accomplished by either lowering the decomposition temperature of the chemical blowing agent by using an activator such as zinc oxide and/or reducing the temperature of the oven. © 2003 Wiley Periodicals, Inc. Adv Polym Techn 22: 280–296, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.10056
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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 | 0.000 |
| 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".