Mechanical Recycling of Crosslinked High-Density Polyethylene (xHDPE)
Bibliographic record
Abstract
This study introduces a mechanical recycling technique for crosslinked high-density polyethylene (xHDPE) using cryogenic pulverization and compression molding. This method is shown to effectively transform xHDPE into valuable fillers for recycled HDPE (rHDPE(B)) sourced from recycled bottles using different concentrations (15–60%) and particle sizes (0–250 µm, 250–500 µm, and 500–1000 µm). In particular, the recycling method significantly reduced the gel content from 60.5% to 41.8% for the 0–250 µm particles, indicating partial decrosslinking. Morphological analysis revealed good interfacial adhesion between rHDPE(B) and recycled xHDPE (r-xHDPE), improving the overall performance and resulting in a balanced combination of properties from both materials. The r-xHDPE samples exhibited improved thermal stability. While particle size had minimal effect on material properties, increasing its concentration significantly improved impact strength (612%) with a slight (3%) reduction in density at 60% 500–1000 µm particles. This research underscores the possibility of recycling crosslinked polymers and highlights the need for further studies to optimize the material properties and expand the methodology to a wider range of polymers.
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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".