The effect of fibre and coupling agent content on the mechanical properties of hemp/polypropylene composites
Bibliographic record
Abstract
Composites made from hemp and polypropylene were prepared in order to determine the effect of fibre and coupling agent content on their mechanical properties. The samples were prepared by compression molding after an initial melt blending and homogenization step in an internal batch mixer. Different fibre contents (0, 10, 20 and 30 wt%) and sizes (355 and 500 μm) were used with two coupling agents: maleic anhydride polypropylene (MAPP) pellets and wax. For each case, MAPP concentrations between 0 and 7 wt% (fibre basis) were added to determine the optimum amount maximizing mechanical properties. The fractured surfaces of these composites were investigated by scanning electron microscopic technique (SEM) to investigate the fibre/matrix interfacial bonding. The mechanical properties of the composites were characterized in tensile, torsion, and flexion and the results showed that coupling agent addition has a positive effect on all moduli with an optimum content ranging between 2 and 4 wt%. It was also found that the coupling agent wax was more effective that the pellets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".