Studies on the Water Absorption Properties of Short Hemp—Glass Fiber Hybrid Polypropylene Composites
Bibliographic record
Abstract
Hemp fiber is one of the inexpensive and readily available bast natural fibers and hemp-fiber reinforced polymer composite products have gained considerable attraction for automotive interior products. Though extensive research has been made on the performance evaluation of these composite materials, not much data is available on the moisture absorption of the composites, which restricts their use in exterior applications. This study aims to investigate the moisture absorption of short hemp fiber and hemp-glass hybrid reinforced thermoplastic composites to study their suitability in outdoor applications. The water absorption properties and its effect on the tensile properties of hemp and hemp/glass fiber hybrid polypropylene (PP) composites prepared by an injection molding process were investigated. Effect of hybridization on the water uptake and the kinetics of moisture absorption of the hemp fiber composites were evaluated by immersing the hybrid composite samples in distilled water at different temperatures, of 40, 60 and 80 ° C. The composites showed a Fickian mode of diffusion; however, a deviation was observed at higher temperature and may be attributed to the microcraks developed at the interface and dissolution of the lower molecular weight substances from the natural fibers. Equilibrium moisture content (M m ) showed that water up take of 40 wt% hemp fiber reinforced PP composites was highest and incorporation of glass fiber decreased the water uptake significantly (40%). Equilibrium moisture content was found to be independent of temperature, while diffusion coefficient (D) was increased with temperature. Effect of water absorption on the tensile properties of the composites showed that there is a significant reduction in strength and stiffness. It was observed that hybridization with glass fibers did not have any significant effect on the strength properties of the aged samples. The tensile properties of the re-dried aged samples showed an increased retention of strength properties after drying; however a complete recovery of the properties has not been achieved. This indicated that water absorption is not a physical process and permanent damage occurred to the composite after aging.
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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".