Polyethylene Melt Rupture and Slip in Simple Shear: A Visual and Mechanistic Study
Bibliographic record
Abstract
ABSTRACT Melt rupture of a bimodal molecular weight distribution polyethylene is studied under simple shear via flow visualization techniques for the first time. We demonstrated that this catastrophic failure is not exclusive to extensional flows. It was found that melt rupture is a time‐dependent phenomenon occurring after steady‐state plateau in slip velocity and stress. The rupture happens at the three‐phase (polymer‐air‐plate) common line and propagates through the specimen. The common line recedes slightly and stops slipping just before the onset of rupture. The presence of polytetrafluoroethylene lubrication (low surface energy coating) changes the nature of the slip mechanism toward adhesive failure and accelerates melt rupture in terms of time‐to‐rupture‐onset (at the same nominal shear rate). Surface roughness reduces the time to rupture onset but without affecting the nature of the slip. A time‐dependent phenomenon at the interface like fractionation or changes in conformation and entanglement density of the interfacial chains is likely the reason for the transition from slip to melt rupture. This conclusion holds substantial industrial relevance, especially since the prevailing approach to prevent rupture involves promoting slip and reducing stress. However, our research demonstrates that even after achieving a relatively high steady‐state slip velocity, rupture can occur.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".