Multiphase morphology control as a robust route to recycling mixed plastic waste
Bibliographic record
Abstract
Plastics are ubiquitous and represent the most intensely used class of materials worldwide. However, they are recycled at notoriously low rates principally because different plastic types must first be identified in the waste stream and separated. Due to their mutual immiscibility, they are largely recycled as a quasi-pure plastic. Here we demonstrate an approach to directly recycle this very problematic mixed plastic waste (MPW) by combining it with a highly continuous carrier system of recycled polypropylene (rPP) and recycled polyethylene (rPE). Through an effective control of the rPP/rPE interface, the mixed plastic waste segregates during one-step melt processing in a stable fashion, according to spreading theory. The MPW components segregate into the rPP phase except for the polyethylene portion which goes into the rPE phase, as evidenced by AFM-IR. This controlled segregation of MPW allows the mechanical integrity to be borne by the principal co-continuous rPP/rPE interface. The final rPP/rPE/MPW material, containing 30% mixed plastic waste, exhibits properties, including impact strength, that are very similar to recycled polypropylene and, critically, can be further recycled multiple times with very little property loss.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".