Production of Thermoplastic Elastomers Based on Recycled PE and Ground Tire Rubber: Morphology, Mechanical Properties and Effect of Compatibilizer Addition
Bibliographic record
Abstract
Abstract Constant growth of waste polymers around the world leads to several environmental problems. This is why solutions to reuse these high amounts of materials available must be developed. In this work, highly filled (up to 90 wt.%) recycled polyethylene (R-PE)/ground tire rubber (GTR) thermoplastic elastomers were prepared by extrusion compounding and injection molding. To improve on processability and overall properties, two copolymers (Engage 8180 and Vestenamer 8012) were added as compatibilizers for comparison. SEM results showed that compatibilizer addition changed the blend morphology. In all cases, the mechanical properties in tension and flexion decreased with GTR addition. It was also observed that the addition of a copolymer improved on some properties (such as elongation at break), but Engage 8180 showed better compatibilization effect than Vestenamer 8012 which was confirmed from SEM analysis, while other properties (tensile strength, Young's and flexural modulus) were reduced due to lower GTR and compatibilizer moduli. For impact strength, negligible variation was observed below 40 wt.% GTR. However, the samples did not break for GTR contents above 60 wt.%. Density increased with GTR content, while Shore A and D hardness decreased. Overall, the addition of a compatibilizer mostly enabled to produce compounds at higher GTR contents (above 70 wt.%). From the result obtained, it can be concluded that recycled materials can be used to produce blends with reasonable quality for automotive, packaging and construction applications since the mechanical properties can be optimized via formulation over a very wide range of GTR (0–90 wt.%).
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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".