Melt fracture of linear low-density polyethylenes: Die geometry and molecular weight characteristics
Bibliographic record
Abstract
The melt fracture phenomena of three linear low-density polyethylenes are investigated as a function of die geometry (capillary, slit, and annular) and molecular weight and its distribution. The onset of melt fracture instabilities is determined by using capillary rheometry, mainly studying the extrudate appearance using optical microscopy. It is found that the onset of flow instabilities (melt fracture phenomena) is significantly affected by die geometry and molecular weight characteristics of the polymers. Use of annular die eliminates the stick-slip transition (oscillating melt fracture) and delays the onset of sharkskin to higher values of shear rate and shear stress. Moreover, it is shown that the molecular weight characteristics of the polymers are well correlated with critical conditions for the onset of flow instabilities based on a criterion proposed in the literature [A. Allal et al., “Relationships between molecular structure and sharkskin defect for linear polymers,” J. Non-Newtonian Fluid Mech. 134, 127–135 (2006) and A. Allal and B. Vergnes, “Molecular design to eliminate sharkskin defect for linear polymers,” J. Non-Newtonian Fluid Mech. 146, 45–50 (2007)].
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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".