Synthesis, Characterization, and Viscoelastic Properties of High Molecular Weight Hyperbranched Polyglycerols
Bibliographic record
Abstract
Very high molecular weight ( M n up to 700 000) and narrowly polydispersed (PDI = 1.1−1.4) hyperbranched polyglycerols (HPG) were synthesized by ring-opening multibranching polymerization of glycidol using dioxane as an emulsifying agent. Broader molecular weight distributions with low molecular weight fractions were obtained when diglyme was used as the emulsifying agent. But the low molecular weight fractions could be removed by dialysis. Isolated yields in both the cases were 70−90%. The different result in the case of dioxane may be due to faster cation exchange which leads to low polydispersites. HPGs of various molecular weights were characterized by a GPC system coupled with a multiangle laser light scattering detector and a triple detector array. The intrinsic viscosities were low for these polymers and did not increase with molecular weight. The dimensions of these polymers ( R g, R h, R η ) and their dependence on molecular weights are described. The hydrodynamic radii were very small with dimensions similar to those of dendrimers. Our results show that these polymers are very compact and have spherical conformations in water with no indications of aggregate formation. The melt viscoelastic properties were also studied. Despite their self-similar structures, depending on the type of solvent used to synthesize them (diglyme vs dioxane), topologically restricted configurations are produced that result in completely different entanglement dynamics.
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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".