Rheological and Functional Properties of Mechanically Recycled Post-Consumer Rigid Polyethylene Packaging Waste
Bibliographic record
Abstract
The properties of recycled post-consumer rigid polyethylene packaging waste were studied, using sorted waste washed in the laboratory with water alone and with added detergent, and compared with large-scale high-intensity washed flakes. The washed flakes were compounded using three different temperature profiles in a twin-screw extruder and then injection molded. A higher compounding temperature reduced the thermo-oxidative stability, the average molecular mass, and the viscosity of the samples. Rheological measurements suggested that changes in chain branching occurred at different compounding temperatures. The strength and the elongation at break were also influenced by the compounding temperature in both the molten and solid states. Detergent washing maintained the thermo-oxidative stability in contrast to washing with water. The large-scale washed samples had a relatively high thermo-oxidative stability, a higher melt elasticity, and a lower elongation at break in both the molten and solid states than the laboratory-scale washed samples. The thermal properties, melt elasticity, Young's modulus, yield stress, and yield strain of the samples were not, however, significantly affected by either the compounding temperature or the washing medium and intensity. The results indicated that recycled post-consumer rigid polyethylene packaging waste has properties that can support further applications in new products.
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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 | 0.001 |
| 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".