Hybrid biocomposites with enhanced thermal and mechanical properties for structural applications
Bibliographic record
Abstract
ABSTRACT The current work focuses on enhancing the mechanical and thermal properties of sisal fiber reinforced composites that were previously used in developing interior automotive trims. In order to extend their use in other structural applications, two hybrid biocomposites with the combination of sisal (SF) and glass fiber (GF)‐SF20/GF10 and SF10/GF20 were blended with polypropylene via extrusion and injection molding process. Critical material properties such as density, fogging, acoustic, mechanical, thermal, and rheological properties were evaluated and results were analyzed using ANOVA. Hybridization of SF and GF enhanced flexural strength and thermal properties of the biocomposites by 33 and 19%, respectively, while no significant change in acoustic, impact and rheological properties were observed. The properties of the hybrid biocomposites were compared with the material specification of a battery tray and it was found that these hybrid biocomposites could be better alternative materials in structural applications. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42452.
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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) | 0.001 | 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".