Injection‐molded short hemp fiber/glass fiber‐reinforced polypropylene hybrid composites—Mechanical, water absorption and thermal properties
Bibliographic record
Abstract
Abstract Natural fiber‐based thermoplastic composites are generally lower in strength performance compared to thermoset composites. However, they have the advantage of design flexibility and recycling possibilities. Hybridization with small amounts of synthetic fibers makes these natural fiber composites more suitable for technical applications such as automotive interior parts. Hemp fiber is one of the important lignocellulosic bast fiber and has been used as reinforcement for industrial applications. This study focused on the performance of injection‐molded short hemp fiber and hemp/glass fiber hybrid polypropylene composites. Results showed that hybridization with glass fiber enhanced the performance properties. A value of 101 MPa for flexural strength and 5.5 GPa for the flexural modulus is achieved from a hybrid composite containing 25 wt % of hemp and 15 wt % of glass. Notched Izod impact strength of the hybrid composites exhibited great enhancement (34%). Analysis of fiber length distribution in the composite and fracture surface was performed to study the fiber breakage and fracture mechanism. Thermal properties and resistance to water absorption properties of the hemp fiber composites were improved by hybridization with glass fibers. Overall studies indicated that the short hemp/glass fiber hybrid polypropylene composites are promising candidates for structural applications where high stiffness and thermal resistance is required. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2432–2441, 2007
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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".