Mechanical Properties of Polymer Composites Reinforced with Alkaline-Treated Natural Fibre
Bibliographic record
Abstract
The mechanical characteristics of a high impact polyethylene composite (HIPC) reinforced with abaca fibre (AF) are investigated in relation to fibre loading. An alkaline behaviour was used to improve the characteristics of the abaca fibre. With a fibre length of 100 mm, five different fibre loadings of the abaca fibre were used to create the samples of the composite (25, 35, 45, 55, and 65 wt percent). The object was made using compression moulding with unidirectional fibre orientation. The influence of fibre loading was investigated using tensile, hardness, and density tests. In an experiment, it was shown that with 55 percent fibre loading, tensile strength was 312 percent higher than without, and Young’s modulus was 545 percent higher than without. While this was happening, the hardness and density of the AF/PE composites were found to be quite similar, with minor increases from 25 wt percent to 65 wt percent AF loading in comparison to the control sample’s zero wt percent AF loading. 67.42 Shore-D and 1.014 g/cm3 are the highest values. The alkaline treatment of the AF/PE composite had a substantial influence on mechanical characteristics, according to the findings.
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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".