Effect of particle size, fiber content, and surface treatment on the mechanical properties of maple-reinforced LLDPE produced by rotational molding
Bibliographic record
Abstract
In this work, composites based on linear low-density polyethylene and maple wood fibers with and without surface treatment with maleated polyethylene (MAPE) were prepared by dry blending, followed by rotomolding to study the effect of particle size, fiber content, and surface treatment. From the samples produced, a complete characterization of the morphological and mechanical properties was performed. The results obtained showed that MAPE surface treatment improved the fiber–matrix interface quality, which improved the homogeneity, the thermal stability, and the mechanical properties of the composites. The results showed that the effect of particle size was significant as the tensile modulus increased by 7%, 40%, and 73% for 125–250, 250–355, and 355–500 µm at 30 wt% of maple fibers. The tensile strength also increased by 114% at the same fiber loading (30 wt%) when the particle size increased from 125–250 µm to 355–500 μm. Finally, the impact strength with 355–500 µm particles was 52% higher than for 125–250 µm particles at 30 wt%
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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) | 0.001 | 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".