Auto-hybridization of Polyethylene/Maple Composites: The Effect of Fiber Size and Concentration
Why this work is in the frame
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Bibliographic record
Abstract
This work investigated the effect of maple fiber size and content on the auto-hybridization of linear low density polyethylene (LLDPE) composites. The samples were compounded by twin-screw extrusion and molded by compression molding. Different fiber loadings (5 to 20% wt.), fiber sizes (0-425 microns) and size ratios (30/70, 50/50, 70/30 of short, medium, and long fibers) were used to prepare the auto-hybrid composites with 3% of coupling agent (maleated polyethylene). Micrographs and impact strength results showed that the fracture in auto-hybrid composites is mostly dependent on the longer fibers. At 10% wt. the optimum ratio was 30/70 of shorter/longer fibers, which improved tensile strength (20%), tensile modulus (20%), and impact strength (13%) compared with composites with a single fiber size. But at 20% wt., tensile modulus increased by 30% and torsion modulus by 40% above the rule of hybrid mixtures (RoHM) at a 70/30 ratio of shorter/longer fibers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it