Impact of molecular architecture and draw ratio on enhancement of targeted mechanical properties of machine direction oriented polyethylene films produced after blown film extrusion
Bibliographic record
Abstract
Conventional multi-material multi-layer flexible packaging offers excellent properties. However, it has recycling challenges, necessitating a shift to mono-material multi-layer flexible packaging for example all-polyethylene (PE) packaging which can be tailored through various synthesis and processing methods for different layers. In this work, we study how the key molecular properties (number-average molecular weight ( M n ), weight-average molecular weight ( M w ), molecular weight distribution (MWD), comonomer content (short chain branching)) and machine direction orientation (MDO) process draw ratio (MDX) influence the final morphology and mechanical properties of MDO-PE films which are intended as the outer layer of mono-material all-polyethylene multi-layer flexible packaging. Five PE grades and various blends were extruded and blown into films. Selected blown films were machine direction oriented to obtain the final MDO-PE films. Furthermore, one selected PE blown film was processed at different MDO process draw ratios while keeping other process parameters constant. From the molecular properties point of view, the higher molecular weight fractions provide a higher possibility for uniform stretching whereas lower molecular weight fractions provide a higher natural draw ratio and therefore higher modulus and stiffness enhancement. Further, the results show that increasing MDO process draw ratio leads to more fibrillation and increased crystallinity. Consequently, the tensile modulus and stiffness at the higher draw ratios increase as well and are comparable to conventionally used polymers in outer layers of multilayer flexible packaging. Thus, this work demonstrates that MDO-PE films with enhanced modulus can provide sufficient stiffness for the design of outer layer of mono-material multi-layer all-PE packaging which presents higher potential for mechanical recyclability.
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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 | 0.000 | 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".