Novel Biodegradable Cast Film from Carbon Dioxide Based Copolymer and Poly(Lactic Acid)
Bibliographic record
Abstract
Poly(lactic acid) (PLA) and poly(propylene carbonate) (PPC) blends with different levels of chain extender were prepared and cast into films. The effect of chain extender on the mechanical, thermal and barrier properties of the films were investigated. With the inclusion of the chain extender, the compatibility and interfacial adhesion between the two polymer phases were significantly improved by a mean of forming a PLA–chain extender–PPC copolymer. Reactions between the chain extender, PLA and PPC were observed through FTIR study. SEM study also confirmed the improved compatibility and interfacial adhesion. The elongation at break of the compatibilized film with optimal amount of chain extender showed dramatic increase by up to 1940 %. DSC studies revealed that chain extender hindered the crystallization of the film which explained the decrease in both water and oxygen barrier when adding chain extender. PLA was found to be able to enhance both oxygen and water barrier of the blend as compared to neat PPC, while in the case of the blend with chain extender, oxygen and water barrier properties exhibited reduction at the beginning. However, when increasing chain extender concentration, these two barrier performance exhibited an upward trend. It was found that PLA/PPC blend showed much better oxygen barrier property than both parent polymers, which can be ascribed to the acceleration effect of PPC on the crystallization of PLA.
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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".