Reactive extrusion effects on rheological and mechanical properties of poly(lactic acid)/poly[(butylene succinate)‐co‐adipate]/epoxy chain extender blends and clay nanocomposites
Bibliographic record
Abstract
ABSTRACT Poly(lactic acid) (PLA), a biosource, biodegradable polymer, is not suitable for some important polymer processing operations, such as film blowing and blow molding, due to its low melt strength. Moreover, while it has high tensile modulus and strength in the solid state, it exhibits low ductility. The present work is an extension of our earlier effort to improve the processability and mechanical properties of PLA by blending with poly[(butylene succinate)‐ co ‐adipate)] (PBSA), a biodegradable polymer with lower glass transition temperature. We evaluate the influences of incorporation of an epoxy chain extender and nanoclay on the properties of the blend. Since earlier work was conducted in a batch mixer, the influence of melt processing in the twin screw extruder and the differences between products obtained in the extruder and the batch mixer are evaluated and explained. Based on earlier work, the following PLA/PBSA blend ratios of 90:10, 80:20 and 70:30 were selected. All the samples were prepared in the twin‐screw extruder at two different screw speeds (50 and 150 rpm), to evaluate the effects of residence time and shear rates. The morphology and structure of the blends were examined using field emission scanning electron microscopy. Transmission electron microscopy (TEM) and X‐ray diffraction (XRD) were used to evaluate the levels of intercalation and exfoliation in the nanocomposites. The chain extension reaction was evaluated using nuclear magnetic resonance (NMR) spectroscopy and other techniques. Rheological properties (dynamic oscillatory shear and elongational viscosity measurements) and mechanical characteristics of the pure components, blends, and nanocomposites were studied and discussed in light of the composition and morphology of the blends and the nanocomposites. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132 , 42664.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".