Synthesis and Characterization of Hyperbranched Polyacrylamide Using Semibatch Reversible Addition−Fragmentation Chain Transfer (RAFT) Polymerization
Bibliographic record
Abstract
Hyperbranched polyacrylamides (b-PAM) were synthesized using a semibatch RAFT copolymerization of acrylamide (AM) and N,N ′-methylenebis(acrylamide) (BisAM) with continuous feeding of BisAM. Small amounts of chain transfer agent (CTA), 3-benzyltrithiocarbonyl propionic acid, with 1/20 to 1/50 molar ratios to BisAM were used to control gelation during the polymerization. Influences of BisAM addition rate, CTA to initiator molar ratio, and AM concentration were also systematically examined. Hyperbranched structures were analyzed by a triple-detector GPC and NMR measurement. The b-PAM polymers had branching densities from 7.2 to 11.7 branches per 1000 carbons, with contraction factors g ′ of 0.295−0.416 and g of 0.201−0.290, weight-average molecular weights of 5.63 × 10 5 to 1.28 × 10 6 g/mol, and polydispersity indexes of 4.7−8.6. It was found that intramolecular cyclization was significant in the polymerization and a substantial number of cyclic structures were formed in the b-PAM samples. Fractionation of GPC traces having the same numbers of primary chains elucidated that branch points were randomly distributed along primary chain backbones. The semibatch process with combined use of BisAM and CTA provided an effective approach to prepare the b-PAM samples at high conversion under low CTA usage.
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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) | 0.001 | 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".