Mechanical and viscoelastic properties of polyethylene‐based microfibrillated composites from 100% recycled resources
Bibliographic record
Abstract
Abstract In this study, recycled polyethylene (rPE) based microfibrillated composites (MFCs) were developed while incorporating recycled poly(ethylene terephthalate) (rPET) and recycled polyamide 6 (rPA) as the reinforcing fibrillar phases at a given weight ratio of 80 wt% (rPE)/20 wt% (rPET or rPA). The blends were first melt processed using a twin‐screw extruder. The extrudates were then cold stretched at a drawing ratio of 2.5 to form rPET and rPA fibrillar structures. Next, the pelletized drawn samples were injection molded at the barrel temperatures below the melting temperatures of rPET and rPA. The tensile, three‐point bending, impact strength, dynamic thermomechanical, and rheological properties of the fabricated MFCs were analyzed. The effects of injection molding barrel temperature (i.e., 150°C and 190°C) and extrusion melt processing temperature (i.e., 250°C and 275°C) on the generated fibrillar structure and the resultant properties were explored. A strong correlation between the fibrillar morphology and the mechanical properties with the extrusion and injection molding temperatures was observed. Moreover, the ethylene/n‐butyl acrylate/glycidyl methacrylate (EnBAGMA) terpolymer and maleic anhydride grafted PE (MAH‐g‐PE) were, respectively, melt processed with rPE/rPET and rPE/rPA6 blends as compatibilizers. The compatibilizers refined the fibrillar structure and remarkably influenced mechanical properties, specifically the impact strength.
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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".