Effect of poly(lactic acid) molecular weight and composition on the morphology and crystallization behavior of polyhydroxybutyrate/poly(lactic acid) blends
Bibliographic record
Abstract
Abstract This study investigates the effects of molecular weight and crystallinity of polylactic acid (PLA) on the morphology and crystallization behavior of polyhydroxybutyrate (PHB)/PLA blends. Utilizing a solution casting method, we discovered that the molecular characteristics of PLA significantly influence the thermal and structural properties of the blends. The lower molecular weight and amorphous PLA notably broadened the temperature range for PHB's banded spherulite formation, indicating enhanced miscibility. In contrast, semicrystalline PLA variants produced smaller spherulites within large PHB matrices. The high molecular weight PLA had an unusual, relatively low melting point which led to a competition between the molecular weight effect and the supercooling effect regarding the isothermal crystallization kinetics. The blend morphology was observed in thin films in which the usual crystal formation of PHB was severely hindered in the presence of crystalline PLA but could form thin lamellae when the PLA was amorphous. At ultra‐thin thickness, where crystallization is impossible, the amorphous co‐continuous structure of the blends was revealed by melting the film. Our research contributes to the development of advanced biodegradable materials for environmental sustainability, emphasizing the intricate interplay between polymer blend components that can be tuned for specific applications. Highlights The study explores the blend morphology and crystallization of PLA/PHB. The temperature range for PHB's spherulite formation broadens with PLA. PLA's partial miscibility with PHB shifted Tg and caused delayed Tm of PHB. Usual PHB crystal formation is hindered with crystalline PLA. Thin PHB lamellae formed within amorphous PLA and observed via AFM.
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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".