Arborescent polystyrene‐<i>graft</i>‐poly(<i>tert</i>‐butyl methacrylate) copolymers: Synthesis and enhanced polyelectrolyte effect in solution
Bibliographic record
Abstract
Abstract A technique is described for the preparation of arborescent graft copolymers containing poly(tert‐butyl methacrylate) (PtBMA) segments. For this purpose, tert‐butyl methacrylate is first polymerized with 1,1‐diphenyl‐2‐methylpentyllithium in tetrahydrofuran. The graft copolymers are obtained by addition of a solution of a bromomethylated polystyrene substrate to the living PtBMA macroanion solution. Copolymers incorporating either short (Mw ≈ 5000) or long (Mw ≈ 30,000) PtBMA side chains were prepared by grafting onto linear, comb‐branched (G0), G1, and G2 bromomethylated arborescent polystyrenes. Branching functionalities ranging from 9 to 4500 and molecular weights ranging from 8.8 × 104 to 6.3 × 107 were obtained for the copolymers, while maintaining a low apparent polydispersity index (Mw/Mn ≈ 1.14–1.25). Arborescent polystyrene‐graft‐poly(methacrylic acid) (PMAA) copolymers were obtained by hydrolysis of the tert‐butyl methacrylate units. Dynamic light scattering measurements showed that the arborescent PMAA copolymers are more expanded than their linear PMAA analogues when neutralized with NaOH. This effect is attributed to the higher charge density in the branched arborescent copolymer structures. © 2008 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 46: 2335–2346, 2008
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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".