Effect of blending sequence and epoxy functionalized compatibilizer on barrier and mechanical properties of <scp>PBS</scp> and <scp>PBS</scp> / <scp>PLA</scp> nanocomposite blown films
Bibliographic record
Abstract
Abstract This study focuses on developing compostable nanocomposite blown films, aiming to enhance oxygen barrier properties while maintaining good mechanical performance. Polybutylene succinate (PBS) and its blend with polylactic acid (PLA) were selected as matrices for the films. Organo‐montmorillonite Delite®43B (D43B) clay was incorporated to improve oxygen barrier, and random ethylene‐methyl acrylate‐glycidyl methacrylate terpolymer served as a plasticizer and reactive compatibilizer. Different blending sequences were examined to determine the optimal one that led to significant enhancements in both the barrier and mechanical properties of the final nanocomposite blown film. Various techniques, including SEM, TEM, XRD, DSC, oxygen permeability, and tensile testing were employed to characterize the morphology of the compounds and blown films. The results reveal greater oxygen barrier properties depending on the blending sequence. Indeed, a reduction in oxygen permeability exceeding 50% was observed following the addition of 3 wt% of D43B to the PBS/PLA film, selectively localized in the PLA phase. This enhancement further intensified after the addition of 5 wt% of the epoxy functionalized compatibilizer. Highlights Enhancing PLA‐PBS compatibility with the epoxy functionalized compatibilizer led to a reduction in the final film's oxygen permeability. Achieving ideal ductility and barrier balance in films requires a synergistic blend of components: D43B, PLA, PBS, and compatibilizer. Optimizing balanced synergistic effects among compounds depends on the blending sequence method.
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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".