Rheological characterization of long-chain branched poly(lactide) prepared by reactive extrusion in the presence of allylic and acrylic coagents
Bibliographic record
Abstract
Reactive extrusion of poly(lactide) (PLA) is implemented to introduce branching, through grafting of multifunctional coagents in the presence of free-radicals. Two types of coagents, allylic and acrylate-based, are compared by analyzing the melt-state linear viscoelastic properties, in combination with triple detection size-exclusion chromatography. The coagent-modified PLA compounds exhibit substantially higher zero shear viscosity, pronounced shear thinning, and higher activation energies for flow when compared to the neat linear PLA. The accompanying increases in the molar mass, broadening of the dispersity, and appearance of high molar mass tails are attributed to the presence of branched architectures. The pronounced deviations from the linear Mark–Houwink plot suggest that long-chain branched structures are generated through the combination of the trifunctional coagents with the PLA macroradicals. The allylic coagent, triallyl mesate (TAM) is substantially more effective in introducing branched structures at low concentrations. On the other hand, the highly reactive acrylate-based coagents are prone to oligomerization in the presence of peroxide resulting in a separate phase, leading to reduced branch density compared to TAM.
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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".