Toughening of Biodegradable Poly(3-hydroxybutyrate-<i>co</i>-3-hydroxyvalerate)/Poly(ε-caprolactone) Blends by In Situ Reactive Compatibilization
Bibliographic record
Abstract
)-trione (TAIC) and peroxide. The compatibility between the two biodegradable polymers was significantly improved only when TAIC and peroxide work together, as evidenced by the decreased PCL particle size and blurred interfacial gap between the PHBV and PCL. The mechanical, thermal, morphological, and rheological properties of the compatibilized blends were studied and compared to the blends without TAIC and peroxide. At the optimal TAIC content (1 phr), the elongation at break of the compatibilized blends was 380% that of the PHBV/PCL blend without any additives and 700% that of neat PHBV. The improved interfacial compatibility, decreased PCL particle size, and uniform PHBV crystals are all factors that contribute to improving the toughness of the blend. Through Fourier transform infrared (FTIR) and rheological studies, the reaction mechanism is discussed. The study shows that PHBV and PCL are cross-linked by TAIC, resulting in the formation of a PHBV-PCL co-polymer, which improves the compatibility of the blend. The biodegradable polymer blends with high crystallinity and improved toughness prepared in this study are proposed to be used in sustainable packaging or other applications.
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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".