Influence of fiber concentration and length on the dielectric, mechanical, and thermal properties of maple wood fiber-reinforced polypropylene
Bibliographic record
Abstract
Natural fiber-reinforced polymer composites are gaining popularity due to their sustainability and enhanced properties compared to pure polymers. Recently, these composites have been utilized as dielectric materials. In this study, polypropylene (PP) reinforced with maple wood fibers of different lengths (50, 75, and 100 µm) and various fiber concentrations (5%, 10%, 15%, and 20%) were examined. The effects of fiber length and concentration on the dielectric, mechanical, and thermal properties were investigated. All composites exhibited a higher dielectric constant and conductivity than pure PP, along with a lower loss factor. This suggests that adding maple wood fibers generally enhances the dielectric properties. As fiber concentration increases, the dielectric constant tends to rise while the loss factor tends to decrease. TGA results indicated that adding more fibers reduces thermal stability at low temperatures but increases stability at high temperatures. Mechanical testing revealed an increase in strength but a decrease in elongation. However, fiber length did not significantly impact the mechanical properties. SEM analysis showed a uniform distribution of fibers at 5% weight that improves strength, while a 20% weight leads to clustering that weakens the composite.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".