Waste valorization in sustainable engineering materials: Reactive processing of recycled carpets waste with polyamide 6
Bibliographic record
Abstract
Waste resources utilization is of utmost importance today to promote sustainable development and minimize pollution. However, it remains a great challenge to reuse, recycle and turn post-consumer wastes into value-added products. Here, we demonstrate a strategy to reprocess post-consumer recycled carpet waste (PCRC) (containing polyamide, polypropylene and other additives and reinforcing agents) with polyamide 6 (PA 6) at different weight ratios through reactive extrusion. The phase adhesion of the PCRC and PA 6 was improved significantly with the aid of poly(ethylene-octene)-grafted-maleic anhydride copolymer (POE-g-MA) and epoxidized styrene-acrylic copolymer (ESAC). Superior notched impact strength and elongation at break were observed when the blends were modified with POE-g-MA and a small amount of chain extender ESAC (0.5–2 phr). Morphological characterization showed a decrease in PCRC droplets size and enhanced its dispersion in the PA 6. FTIR analysis showed an enhancement of interfacial compatibilization between PA 6 and PCRC by the interaction between maleic anhydride of POE-g-MA and epoxy group of ESAC with polyamide functional group through melt mixing. The effective compatibilization of the blends was also evident from thermal and rheological analysis. The results revealed the possible reuse and utilization of recycled carpet for different polymer blends and composites fabrication with high recycled content for various applications.
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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) | 0.001 | 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 | 0.001 |
| 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".