Toughening of Cocontinuous Polylactide/Polyethylene Blends via an Interfacially Percolated Intermediate Phase
Bibliographic record
Abstract
It will be shown that an interfacially percolated rubbery phase in a cocontinuous polylactide (PLA)/linear low-density polyethylene (LLDPE) blend results in a significant increase in the impact strength. All blends possess a tricontinuous phase morphology in which poly(ε-caprolactone) (PCL), poly(ethylene–methyl acrylate) (EMA), and ethylene–methyl acrylate–glycidyl methacrylate (EMA-GMA) percolate at the interface of PLA/LLDPE but offer different toughening and compatibilization effects. Among these components, the addition of EMA-GMA to the binary PLA/LLDPE blend reduces the cocontinuous PLA/LLDPE phase thickness from about 25 to 5 μm and yields a very tough material with an impact strength of about 515 J/m, which is approximately 13 times greater than the original cocontinuous PLA/LLDPE blend and more than 32 times that of PLA. The ternary blends show significant improvements in the impact strength within the tricontinuous region; however, the principal differences in the toughening effects are attributed to interfacial interactions between the phases. The interconnected network of the rubbery phase is expected to percolate the stress field throughout the tricontinuous system and reduce the detrimental dilatational stress in the bulk blend.
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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".