Solvent‐assisted anionic ring opening polymerization of glycidol: Toward medium and high molecular weight hyperbranched polyglycerols
Bibliographic record
Abstract
ABSTRACT Hyperbranched polyglycerols (HPGs) are globular structures with a large number of functionalizable hydroxyl groups and have excellent in vitro and in vivo biocompatibility profiles comparable to polyethylene glycol. This work introduces a facile method for the synthesis of medium molecular weights (Mws) (50–300 kDa) HPGs, which has been difficult to synthesize with low polydispersity, with the assistance of solvents by ring opening polymerization. The influence of different solvents (1,4‐dioxane, tetrahydropyran (THP), ethylene glycol diethyl ether (EGDE) and decane), solvent to glycidol ratio, concentration of glycidol and the time of polymerization on Mw and polydispersity of HPGs has been studied. The Mw and polydispersity of HPGs are significantly affected by the nature of the polymerization phase (homogeneous or heterogeneous) and chemical structure of the solvent. The differences in the solvation of the potassium cations and change in the nucleophilicity of the alkoxide anion in various solvents may be responsible for the changes in Mw and PDI of the HPG. The Mw of the HPG decreases in the order 1,4‐dioxane > THP > EGDE >decane. The microstructure, solution and thermal properties of the HPG do not depend on the nature of solvent. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013, 51, 2614–2621
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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) | 0.000 | 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".