Fundamental foaming mechanisms governing the volume expansion of extruded polypropylene foams
Bibliographic record
Abstract
Abstract This article describes the fundamental foaming mechanisms that governed the volume expansion behavior of extruded polypropylene (PP) foams. A careful analysis of extended experimental results indicated that the final volume expansion ratio of the extruded PP foams blown with butane was governed by either the loss of the blowing agent or the crystallization of the polymer matrix. A charge coupling device (CCD) camera was installed at the die exit to carefully monitor the shape of the extruded PP foams. The CCD images were analyzed to illustrate both mechanisms, gas loss and crystallization, during foaming at various temperatures, and the maximum expansion ratio was achieved when the governing mechanism was changed from one to the other. In general, the gas loss mode was dominant at high temperatures and the crystallization mode was dominant at low temperatures. When the gas loss mode was dominant, the volume expansion ratio increased with decreasing temperature because of the reduced amount of gas lost. By contrast, when the crystallization mode was dominant, the expansion ratio increased with increasing temperature because of the delayed solidification of the polymer. The processing window variation with the butane concentration, the change in the temperature ranges for the two governing modes, and the sensitivity of melt temperature variations to the volume expansion ratio are discussed in detail on the basis of the obtained experimental results for both branched and linear PP materials. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 2661–2668, 2004
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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 | 0.000 |
| 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".