Effects of fiber content and extrusion parameters on the properties of flax fiber - polyethylene composites
Bibliographic record
Abstract
Extrusion compounding addresses such problems as the non-homogeneity of the mixture and separation of fiber from the polymer during rotational molding, which consequently affect the mechanical and physical properties of the resulting composites. Using triethoxyvinylsilane as chemical pre-treatment on flax fibers and linear low density polyethylene (LLDPE) and high density polyethylene (HDPE) as polymer matrices, this study focused on the effects of flax fiber content (0%, 12.5% or 25%) and extrusion parameters such as barrel zone temperatures (75-110-120-130-140°C or 75-120-130-140-150°C) and screw speed (110 or 150 rpm) on the extrudate and composite properties (extrudate color, extrudate density, extrudate melt flow index, extrudate morphology, composite color, composite density, composite morphology, composite tensile strength and composite water absorption). A mixture of chemically pre-treated flax fibers and powdered polyethylene matrices underwent extrusion compounding using a twin-screw extruder. The extrudates were then pelletized, ground, rotationally molded and cut into test specimens (composites). The mechanical and physical properties of both the extrudates and the composites from different treatments were then measured and compared. Using multiple linear regression, models were generated to show quantitatively the significant effects of the process variables on the response variables. Finally, using response surface methodology and superposition surface methodology on the preceding data, the following optimum values for fiber content and extrusion parameters were determined: for LLDPE composites, fiber content = 6.25%, temperatures = 75-117.3-127.3-137.3-147.3°C, screw speed = 117.5 rpm; for HDPE composites, fiber content = 5.02%, temperatures = 75-118.1-128.1-138.1-148.1°C, screw speed = 125.56 rpm.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".