Characterisation of coir fibre hybrid composites reinforced with clay particles and glass spheres
Bibliographic record
Abstract
Hybrid composite materials were fabricated using an optimum coir fibre with functionalised clay and glass spheres using a vacuum-assisted resin transfer moulding. The coir fibres were treated with 10% sodium hydroxide (NaOH) to improve their bonding properties by removing the cellulose and lignin found on the fibre surface. Clay functionalisation was done using 3-aminopropyltriethoxysilane at different ratios and obtained an optimum ratio of 1 g clay: 2 g silane. Composite specimens were fabricated using epoxy and coir fibre at 7%, 10%, 15% and 20% volume fractions, respectively. Based on the mechanical properties, an optimum volume fraction of 15% coir fibre was selected to fabricate the hybrid composites with functionalised clay and glass spheres reinforcements, respectively. These composite specimens were then characterised to obtain their tensile, flexural and impact properties. From the results, it was realised that hybrid composites containing 4% functionalised clay particles and 8% glass spheres have superior mechanical properties. The reason behind the improved properties might be due to the reinforcing effect of the particles, which improved the load transfer between the fibre and the matrix.
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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".