Sintering of Ground Rubber Tire (GTR) powder
Bibliographic record
Abstract
One method of recycling used tires is to shred them into GTR powder, which are subsequently reused by blending with other materials such as virgin rubber, thermoplastics (as a filler) and asphalt (as a binder). Recycling 100% GTR through compression molding has been sparsely studied over the last three decades. Understanding the solid-state sintering of the GTR powder is key to optimizing the process parameters to yield desired properties and is the objective of this study. The sintering was first studied using a rheometer and a 12.6 mm diameter compression mold under non-isothermal conditions. Sintering of the GTR powder increased beyond 150C and completed by 250C. TGA (Thermogravimetric Analysis) confirmed increase in the degradation of the GTR powder beyond 250C. DSC (Differential Scanning Calorimeter) analysis indicated a string exothermic peak beyond 180C, with possible contributions coming from both re-vulcalization (cross-linking) and degradation. Compression molding of tensile test coupons using temperature, pressure, and time chosen based on rheometer results. The molding conditions of 250C and 11.5 MPa resulted in maximum strength (~6.5 MPa) and maximum failure strain (~300%). Further research is on-going to improve these values and will be discussed during the conference.
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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) | 0.003 | 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".