Synergistic Effects of Silane-Treated Calotropis and Ziziphus Fillers on Epoxy Composite Properties, pp. 112-133
Bibliographic record
Abstract
Composites made using natural fibers (NF) and other sustainable materials have recently gained a lot of focus to improve thermal, mechanical, and tribological properties.Using a wide range of criteria, this study inspected the efficacy of epoxy composites strengthened with silane-treated (ST) Calotropis gigantea fiber, and filled with Ziziphus mauritiana seeds.Comprehensive mechanical, thermo-gravimetric, tribological, and morphological testing were performed on the composites specimens and other examinations including Fourier transform infrared spectroscopy and X-ray diffraction was also conducted.The aim of these investigations is to determine the effect of ST and Ziziphus mauritiana seeds (ZMS) concentration on the composites.The mechanical characterization results showed that silane-treated (ST) composites with a higher concentration of Ziziphus mauritiana Seeds had significantly better tensile strength (TS), impact strength (IS), and microhardness than either the untreated (UT) specimens or those with a lower percentage of ZMS.To be more specific, the D composite sample exhibited the best results, with microhardness measuring 92.4 HV, IS at 31.2 kJ/m2, and tensile strength measuring 121.7 MPa.A lower coefficient of friction (CoF) and improved wear resistance were the results of the tribological analysis of composites ST with an increased ZMS content.Among samples, the composite D showed the least amount of wear loss (60 m) and had the lowest frictional force (4.9N).The thermal characterization analysis demonstrated enhanced thermal stability in the composites treated with silane, namely in the formulations of samples C and D. This indicates an elevated ability to withstand degradation caused by temperature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".