Recycled from waste tires carbon black/high‐density polyethylene composite: Multi‐scale mechanical properties and polymer aging
Bibliographic record
Abstract
Abstract This study addresses the global issue of recycling vehicle rubbish tires by a vacuum pyrolysis process, exploring a novel environmentally responsive approach for thermal decomposition and recovery of the carbon black particles contained in tires (25–30 wt%). Carbon black is typically used for its UV protection in plastics and abrasion resistance in composites and rubbers. This research aims at providing an eco‐responsible alternative to commercial carbon black of fossil origin by recycling the carbon black (rCB) from end‐of‐life tires. A particle reinforced composite material was developed containing rCB and high‐density polyethylene. For comparison purposes, an identical composite was manufactured using commercial carbon black (CB). Accelerated aging studies have been carried out on the materials. Topographic evolution of the samples with aging and oxidation kinetic of the surface and through the thickness were studied. Multiscale mechanical properties have been evaluated for a more comprehensive understanding of the mechanisms involved in the degradation. A comparison of the different materials properties was carried out in order to highlight the various elements linked to the degradation and UV protection of materials. This work helps demonstrating the feasibility of using recycled carbon black particles from waste tires as a high‐performance filler for plastics and composites. Highlights Recycled carbon black (rCB) is an eco approach of revalorizing tire waste. Vacuum pyrolysis successfully allows recovery of reusable rCB. The rCB acts as a photon absorber, limiting degradation of HDPE. The rCB limits the cross‐linking responsible of embrittlement of HDPE. A critical carbonyl index of 20 marks the occurrence of cracks and degradation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".