Dimensional stability, density, void and mechanical properties of flax fabrics reinforced bio-phenolic/epoxy composites
Bibliographic record
Abstract
Due to the growing trend to promote alternative materials, the use of cellulosic fibers as filler/reinforcement in polymer composites has increased in popularity. The objective of this research is to determine the effect of flax fabric loading on the physical and mechanical properties of bio-phenolic/epoxy composites. The composites were fabricated using hand lay-up method in a mould and cured using a hot press. Bio-phenolic/epoxy blend was fabricated as control. The sample was tested for physical, tensile, flexural, impact and morphological properties. The result showed that, increasing the flax fabric loading has increased the water absorption and density of composites. The highest water absorption density was shown by the composite with 50 wt% flax fabric loading which is 3.73% and 1.23 g/cm 3 . In addition, there is no significant difference in void content for all composites. Moreover, the incorporation of flax fabric as reinforcement has improved the mechanical properties of composites. According to the morphological analysis results of the experiments, there was a good bonding interaction between the flax fabric and bio-phenolic/epoxy. The highest tensile strength, tensile modulus and impact strength was shown by composite with 50 wt% flax fabric which was 105.04 MPa, 9.10 GPa and 11.94 kJ/m 2 respectively while composite with 40 wt% showed the highest flexural strength and modulus which was 150.45 MPa and 8.4 GPa respectively. It was concluded that, bio-phenolic/epoxy blend reinforced with 50 wt% flax fabric showed the best overall mechanical properties and it will be used in the future study to fabricate carbon/kevlar/flax reinforced bio-phenolic/epoxy for ballistic helmet application.
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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".