Formation and characterization of polyethylene blends for autoclave‐based expanded‐bead foams
Bibliographic record
Abstract
Abstract Blends of linear‐low‐density polyethylene (LLDPE), low‐density polyethylene (LDPE), and high‐ density polyethylene (HDPE) were foamed and characterized in this research. The goal was to generate clear dual peaks from the expanded polyethylene (EPE) foam beads made from these blends in autoclave processing. Three blends were prepared in a twin‐screw mixing extruder at two rotational speeds of 5 and 50 rpm: Blend1 (LLDPE with 20 wt% HDPE), Blend 2 (LLDPE with 20 wt% LDPE), and Blend 3 (LLDPE with 10 wt% HDPE and 10 wt% LDPE). The differential scanning calorimetric (DSC) measurement was taken at two cooling rates: 5 and 50°C/min. Although no dual peaks were present, the results showed that blending with HDPE has a more noticeable effect on the DSC curve of LLDPE than blending with LDPE. Also, the rotational speed and cooling rate affected the shape of the DSC curves and the percentage area below the onset point. The DSC characterization of the batch foamed blends revealed multiple peaks at certain temperatures, which may be mainly due to the annealing effect during the gas saturation process. POLYM. ENG. SCI., 2010. © 2009 Society of Plastics Engineers
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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 | 0.001 | 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".