Tire-derived reclaimed rubber as a secondary raw material for rubber foams: in the framework of circular economy strategy
Bibliographic record
Abstract
Abstract Improper disposal and accumulation of waste tire rubbers have posed a serious threat to the development of a circular economy, a sustainable environment, and human health. In light of the drawback of the current waste management of waste tires, the recycling and transformation of reclaimed rubber (RR) into valuable end products has received significant attention from industries and the academic field. Herein, we propose a facile method to reuse RR in developing closed-cell elastomeric foams based on ethylene propylene diene rubber (EPDM). Rheometry results revealed that the introduction of RR up to 20 phr, increased the cure rate from 11.7 to 13.48%/min, reduced curing time from 12.21 to 9.3 min and also increased ultimate torque from 6.51 to 7.24 N.m. Morphological studies indicated that the RR increased the cell density from 12 to 78 cell/mm3 and reduced the number average cell size from 940 to 110 µm. The mechanical results indicated that the introduction of RR could be a feasible alternative for the fabrication of high-performance EPDM foams with improved hardness and resilience. By increasing RR content of EPDM/RR foams, the relative density and cell density of EPDM/RR foams increased, while cell size decreased. The introduction of 10 phr of RR, increased the hardness and resilience of the EPDM foam by 37 shore A and 68%, respectively. The research verified that the attempt to use RR to produce a good foam structure was found to be successful. The results open a way for EPDM/RR foam composites to be applied for sealing and gasket industries as an eco-friendly replacement for virgin products. Highlights • Use of reclaimed rubber from waste tires as secondary raw material for EPDM rubber foams • Tire-derived reclaimed rubber/EPDM closed-cell foams support the circular economy of waste tires • Tire-derived reclaimed rubber/EPDM closed-cell foams exhibit superior mechanical properties at the low cost
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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 | 0.001 |
| 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".