Performance Improvement of Natural Fibre-Composites using Clay Nanocomposites
Bibliographic record
Abstract
The role of nanoclays on the performance improvement of structural composites made from flax fibers was investigated. The nanoclays were at first dispersed in the polymer matrix before the impregnation the flax fibers. The results obtained for the epoxy based composites demonstrate that specific treatment of the fiber surface can bring up the performance of composites such as the tensile strength, tensile modulus and the interfacial strength of the composites. However, the level of improvement on the properties of the composites is much better in the presence of dispersed nanoclays. In principle, the composite strength and modulus are mainly controlled by the fibers if the fiber-matrix interface is optimized. Thus the observed improvements in composite strength and modulus can be interpreted by the nanoclays role in the improvement of the load transfer from the matrix to the fiber and hence enhancement of the interfacial properties. This study confirmed that nanoclays can be used to upgrade the mechanical performance of natural fiber composite and also can reduce the gas diffusion through the material resulting in the enhancement of the fire resistance.
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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".