Sustainable Reuse of Waste Tire Textile Fibers (WTTF) as Reinforcements
Bibliographic record
Abstract
Waste tire textile fibers (WTTF), as a by-product (10-15% by weight of tires) of end-of-life tires (ELT) mechanical recycling (grinding), are classified as hazardous wastes and traditionally burnt (thermal recycling) or buried (landfilling), leading to several environmental and ecological issues. Thus, WTTF still represent an important challenge in today's material recycling streams. It is vital to provide practical and economical solutions to convert WTTF into a source of inexpensive and valuable raw materials. In recent years, tire textile fibers have attracted significant attention to be used as a promising substitute to the commonly used natural/synthetic reinforcement fibers in geotechnical engineering applications, construction/civil structures, insulation materials, and polymer composites. However, the results available in the literature are limited, and practical aspects such as fiber contamination (~65% rubber particles) remain unsolved, limiting WTTF as an inexpensive reinforcement. This study provides a comprehensive review on WTTF treatments to separate rubber and impurities and discusses potential applications in expansive soils, cement and concrete, asphalt mixtures, rubber aerogels and polymer composites.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".