Rheological evaluation of metallocene polyethylenes with processing aids by multi‐wave oscillations
Bibliographic record
Abstract
Abstract During the die flow of metallocene polyethylenes, flow instabilities may occur. Namely, wall slip, “sharkskin,” and stick‐slip (pressure oscillations) and gross fracture may be obtained depending on the volume flow rate and die geometry. It was reported that fluoroelastomers and boron nitride powders with hexagonal crystal structure can be used as suitable processing aids in melt extrusion processes. Fluoroelastomers at low concentrations act as die lubricants and may eliminate flow instabilities such as surface and stick‐slip melt fracture. On the other hand, specific boron nitride powders may not only eliminate surface and stick‐slip melt fracture, but also postpone gross melt fracture to higher volume flow rates. In this paper, a way for quantitative differentiation of the influence of polymer processing additives on rheological behavior is shown. Standard material functions show no clear‐cut differences. However, using multi‐wave oscillations with higher strain amplitudes make a quantitative assessment possible. Polym. Eng. Sci. 44:2047–2051, 2004. © 2004 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 | 0.001 |
| 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".