Preparation of pyridine end functionalized copolymers from eutectic mixtures of L-lactide and trimethylene carbonate
Bibliographic record
Abstract
Poly (L-lactide) (PLLA) is a polymer that has several applications in the biomedical area, being used including in controlled-release systems. However, this polymer has certain limitations. One of them is the fact that its degradation products are acidic compromising tissues. Therefore, several studies have been carried out with the objective of incorporating comonomers in its structure. In this context, the trimethylene carbonate (TMC) comonomer has proved to be an excellent choice to overcome the limitations of PLLA, as the degradation products of TMC are not acidic and are well tolerated by the human body. In this work, random copolymers functionalized with a pyridinic binder were prepared, with the monomers L-lactide and trimethylene 1,3-carbonate, via reactions from their eutétic melts. These reactions were carried out under different reaction conditions and with the 1,8-diazabicyclo[5.4.0]undec-7-eno (DBU) organocatalyst. The hydrogen and carbon nuclear magnetic resonance analyses (NMR 1H and 13C) confirmed the structure and functionalization of the copolymers. In addition, it was possible to observe from the composition data, greater incorporation of LLA when the reactions were carried out at room temperature. Gel permeation chromatography (GPC) analysis revealed that the majority of the samples exhibited a monomodal molar mass distribution, with number-average molar masses (Mn) ranging from 4665 to 27 950 g/mol and narrow polydispersity indices (PDI) in most cases. The results of differential scanning calorimetry show a gradual increase in the Tg of the copolymer as the L-lactide content increases.
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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".