Properties of polylactic acid blends with potato thermoplastic starch using maleated polyethylene as a compatibilizer
Bibliographic record
Abstract
Abstract In this study, blends of polylactic acid (PLA) and potato thermoplastic starch (TPS) with and without maleated polyethylene (MAPE) as a compatibilizer were prepared by twin‐screw extrusion followed by compression molding. Different formulations were proposed based on an experimental design to determine the concentration of each component for a specific range of composition: 49%–79% of PLA, 20%–50% of TPS, and 0.5%–2% of MAPE. As a first step, the mechanical properties (tensile, flexural, and impact) were used to determine the best performance of these formulations. Then, the mechanical results were used in an objective function to maximize the blends' properties compared to virgin PLA. The optimal formulation was found to be 67.5% PLA, 32.0% TPS, and 0.5% MAPE. Selected formulations were characterized for their thermal, morphological, and water absorption properties. The results show the possibility of producing sustainable polymers for single‐use 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".