Rheological characterization of polyethylene/polyester recycled tire fibers/ground tire rubber composites
Bibliographic record
Abstract
ABSTRACT The rheological behavior of polyester recycled tire fibers (RTF) mixed with ground tire rubber and linear low density polyethylene (LLDPE) with and without styrene–ethylene–butylene–styrene grafted maleic anhydride (SEBS‐g‐MA) as a compatibilizer was investigated in the melt (small amplitude oscillatory shear) and solid (dynamic mechanical analysis) states. In particular, the effect of RTF content (10, 25, and 50 wt %), extrusion screw speed (110, 180, and 250 rpm), and temperature profiles (extrusion and injection molding) was studied. In general, it was found that the rheological properties in the melt state (modulus and viscosity) of the uncompatibilized samples increased with RTF content, but higher values were obtained when SEBS‐g‐MA was added due to better interfacial coupling. Although similar results were obtained in the solid state, it was shown that melt rheology can better explain the variations as the measurements are more sensitive to the interface quality since the matrix contribution is less important. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46563.
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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 | 0.001 | 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".