Strategies for Achieving Microcellular LDPE Foams in Extrusion
Bibliographic record
Abstract
This paper describes the fundamental process design for achieving microcellular foams using low-density polyethylene (LDPE) in extrusion. Microcellular foams are classified as foams with cell densities larger than 10 9 cells/cm 3 and cell sizes in the order of 10 micrometers. Supercritical CO 2 was used as a blowing agent in microcellular foaming due to its high volatility, which greatly increases thermodynamic instability. Our previous studies have indicated that microcellular foams cannot be produced from pure LDPE in a conventional microcellular extrusion system because of the high activation energy for cell nucleation. To increase the cell-nuclei density, an attempt was made at reducing the free energy for bubble nucleation by heterogeneous cell-nucleation. LDPE blends, with a small amount of polystyrene (PS) and/or a nucleating agent, were employed to induce heterogeneous cell-nucleating spots. The amount of the PS phase was varied to determine the optimum content. Furthermore, the melt strength of LDPE was increased by crosslinking. Microcellular LDPE foams have been successfully obtained in extrusion and the materials and processing windows have been clearly identified. The amount of injected CO 2 was varied in order to investigate its effect on the cell-population density.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".