Mechanical Behaviour of Alkali-Treated Fabric-Reinforced Polymer Matrix Composites
Bibliographic record
Abstract
Polyethylene (PE) was used as a composite material to create a fabric containing 40% pineapple, 30% jute, and 30% cotton fibres by weight. The physical characterisation is carried out, like deterioration and water absorption tests. PE-based composites were shown to have a lower water absorption rate when dipped in deionized water to perform an absorption test. Fabric/PE composites decomposed slowly in the soil during the degradation test. Alkali solution of 5 percent, 7 percent, and 9 percent sodium hydroxide by weight for 60 minutes was studied as alkali impact mechanical characteristics: mechanical testing’s like tensile strength and modulus, elongation at break, bending strength, and modulus. Data investigation exposed that the tensile strength and modulus, elongation at break, bending strength, and composite modulus values were 64 MPa and 871 MPa, 23.14 percent, 45 MPa, and 512 MPa. There were tensile strength and modulus, elongation at break, bending strength, and modulus of the neat polyethylene sheet that were 32Mpa and 342 MPa, 79 percent, 22 MPa, and 234 MPa, respectively. Compared to a polyethylene sheet, composite values for tensile strength and modulus, bending strength, and modulus raised by 107%, 156%, 110%, and 115% as a result of fabric reinforcing.
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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) | 0.002 | 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".