Synthesis of Grafted Polylactic Acid and Polyhydroxyalkanoate by a Green Reactive Extrusion Process
Bibliographic record
Abstract
Grafted polylactic acid (PLA) and polyhydroxyalkanoate (PHA) were synthesized by a reactive extrusion method. The grafted bio-based polymers had either polar functional groups such as hydroxyl (-OH) and polyethylene glycol (PEG) or non-polar functional groups. It was found that grafted biopolymers had significantly reduced melt viscosity, making them more suitable for certain polymer processing such injection molding and fiber spinning. The grafted biopolymers had improved compatibility in blending with other polar polymers such as polyvinyl alcohol and exhibited improved fiber spinning processability in polymer blends. Grafted PHA had a low crystallization rate making continuous reactive extrusion impossible. It was found that a novel co-grafting method, i.e. grafting PHA in the presence of PLA, was effective to overcome the process challenge of PHA. The reactive groups introduced to PLA or PHA can be used for further side chain reactions. The free radical initiated grafting reaction was a green reaction method. It eliminated the use and recovery of organic solvents, the reaction rate was also significantly increased over solution grafting reaction, taking seconds to complete rather than hours.
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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 | 0.001 |
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".