The Interaction Effect of the Design Parameters on the Water Absorption of the Hemp-Reinforced Biocarbon-Filled Bio-Epoxy Composites
Bibliographic record
Abstract
Natural fiber-reinforced composites perform poorly when exposed to moisture. Biocarbon has been proven to improve the water-absorbing behavior of natural fiber composites. However, the interaction effect of the design parameters on the biocarbon-filled hemp fiber-reinforced bio-epoxy composites has not been studied. In this study, the effects of the design parameters (pyrolysis temperature, biocarbon particle size, and filler loading) on the water absorptivity and water diffusivity of hemp-reinforced biopolymer composites have been investigated. Biocarbon from the pyrolysis of hemp and switchgrass was produced at 450, 550, and 650 °C. Composite samples with 10 wt.%, 15 wt.%, and 20 wt.% of biocarbon fillers of sizes below 50, 75, and 100 microns were used. The hemp fiber in polymer composites showed a significant influence in its water uptake behavior with the value of water absorptivity 2.41 × 10−6 g/m2.s1/2. The incorporation of biocarbon fillers in the hemp biopolymer composites reduces the average water absorptivity by 44.17% and diffusivity by 42.02%. At the optimized conditions, the value of water absorptivity with hemp biocarbon and switchgrass biocarbon fillers was found to be 0.72 × 10−6 g/m2.s1/2 and 0.73 × 10−6 g/m2.s1/2, respectively. The biocarbon at 650 °C showed the least composite thickness swelling due to its higher porosity and lower surface area. Biocarbon-filled hemp composites showed higher flexural strength and energy at the break due to the enhanced mechanical interlocking between the filler particles and the matrix materials. Smaller filler particle size lowered the composite’s water diffusivity, whereas the larger particle size of the biocarbon fillers in composites minimizes the water absorption. Additionally, higher filler loading results in weaker composite tensile energy at the break due to the filler agglomeration, reduced polymer-filler interactions, reduced polymer chain mobility, and inadequate dispersion of the filler.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".