Synergistic association of wood /hemp fibers reinforcements on mechanical, physical and thermal properties of polypropylene-based hybrid composites
Bibliographic record
Abstract
Natural fiber-reinforced composites with thermoplastic matrices are gaining prominence in society as their applications are found in varied industries, e.g., automotive and aerospace. A recent trend shows the use of hemp fibers as reinforcements for the manufacture of bio-based composites, which are thermally and dimensionally stable, and durable. In this work, polypropylene (PP) was reinforced with 5, 10, 20, 30, and 40 wt% hemp fibers, having undergone an alkaline treatment, were processed, and investigated. Results showed that the composites made of hemp fibers with PP have exhibited good mechanical properties. A value of 2.12 GPa for young's modulus is achieved from a biocomposites containing 30 wt% of hemp fibers which is significantly higher than the 0.85 GPa of PP matrix. The full potential of hemp fibers as reinforcement for the PP matrix is demonstrated by this maximum, which represents a rise of 149% for the young's modulus and 40% for the tensile strength. Flexural modulus increased of 46%, 165%, and 232% compared to virgin PP at 10, 30, and 40 wt% fiber content. Such stiffness increases were followed by flexural strength increases of 52%, 78%, and 92% relative to virgin PP in the presence of 20, 30, and 40 wt% hemp fibers, respectively. A study was also conducted to evaluate the effects of various parameters on the thermo-mechanical properties of the final composites, which were hybrids made of PP reinforced with both hemp fibers and wood flour. These hybrid bio-composites prepared with 20 and 40 wt% hemp fibers and wood flour and variable ratios of the two reinforcements showed a positive hybridization effect. Nevertheless, the modulus of the hybrid biocomposites reinforced by both fibers, hemp/Wood floor (20/20), is 166% greater than the modulus of unreinforced PP and 34% greater than the Hemp/PP composite with 40% fiber content. Finally, a comparative study shows that the newly formulated hybrid composite has the potential to replace various existing natural fiber-reinforced composites. This study's approach is, although we know, unique.
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 | 0.000 |
| 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".