Study of biodegradable poly(butylene succinate‐co‐adipate) (<scp>PBSA</scp>) maleation: Analysis of grafting, thermal, and rheological behaviour
Bibliographic record
Abstract
Abstract Herein, the effects of varied concentrations of an organic peroxide and maleic anhydride (MA) on the grafting percentage as well as the amount of gel content, rheological, and thermal properties of MA‐grafted‐poly(butylene succinate‐co‐adipate) (PBSA) were analyzed. The grafting was performed by melt extrusion processing. The MA grafting onto the PBSA polymer chains was successfully confirmed through Fourier transform infrared spectroscopy, and the MA‐grafting percentage was quantified by the back titration. Increasing MA and initiator content increased the peak intensity (at 1780 cm −1 ) associated with grafted saturated anhydride MA moieties on the PBSA backbone. Higher concentrations of initiator and MA directly influenced the grafting percentage, reaching to the maximum grafting degree of 2.48%. A greater amount of initiator produced more radicals on the polymer chain, promoting crosslinking reactions, resulting in a higher gel content and complex viscosity. This increased gel content and, thus, higher complex viscosity. Additionally, the increase in gel content affected the thermal stability of the MA‐grafted‐PBSA where the maximum decomposition temperature was increased by ⁓7°C, as a result of the improved crosslinking effect. Higher MA grafting percentage reduced the chain regularity of maleic anhydride grafted PBSA (MA‐g‐PBSA); therefore, the percentage crystallinity decreased. Gaining insight into the impact of MA and initiator concentrations on MA‐grafted‐PBSA can aid in developing composites or blends with enhanced miscibility and performance.
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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".