Impact of Organic and Inorganic Fillers on the Performance of Ternary Biodegradable Poly(Butylene Succinate‐Co‐Butylene Adipate), Poly(Butylene Adipate‐Co‐Terephthalate), and Poly(3‐Hydroxybutyrate‐Co‐3‐Hydroxyvalerate) Blends
Bibliographic record
Abstract
ABSTRACT This study explores a ternary biodegradable blend of bio‐based poly(butylene succinate‐co‐adipate) (bio‐PBSA), poly(butylene adipate terephthalate) (PBAT), and poly(3‐hydroxybutyrate‐co‐3‐hydroxyvalerate) (PHBV). By blending with flexible bio‐PBSA and PBAT, the stiffness enhancement of PHBV makes this biodegradable polymer blend a promising candidate for packaging applications. The blends were processed by melt‐compounding via extrusion, followed by injection molding. The blend is enhanced with fillers including talc, kaolin clays, and soybean meal to evaluate and compare the effects of these fillers on the composite's performance. As an inorganic filler, kaolin outperformed talc and soybean meal, increasing Young's modulus by nearly 18%, impact strength by 20%, and elongation at break by approximately 21% compared with the ternary blend. Additionally, the addition of kaolin improved water vapor barrier properties by approximately 28%, primarily due to increased crystallinity. Rheological analysis also indicated a rise in complex viscosity, reflecting stronger adhesion between the matrix and talc compared to both organic and inorganic fillers. These findings highlight the potential of these composites to meet performance standards of traditional plastics, advancing the use of biodegradable materials in film packaging applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".