pH‐ and temperature‐sensitive statistical copolymers poly[2‐(dimethylamino)ethyl methacrylate‐<i>stat</i>‐2‐vinylpyridine] with Functional succinimidyl‐ester chain ends synthesized by nitroxide‐mediated polymerization
Bibliographic record
Abstract
Abstract Statistical copolymerizations of 2‐(dimethylamino)ethyl methacrylate (DMAEMA) with 2‐vinylpyridine (2VP) with 80 to 99 mol % DMAEMA in the feed utilizing a succinimidyl ester‐terminated alkoxyamine unimolecular initiator (NHS‐BlocBuilder) at 80 °C in bulk were performed. The effectiveness of 2VP as a controlling comonomer is demonstrated by linear increases in number‐average molecular weight versus conversion, relatively low PDI (1.5–1.6 with up to 98% DMAEMA) and successful chain extensions with 2VP. Additional free nitroxide does not significantly improve control for the DMAEMA/2VP copolymerizations. The succinimidyl ester on the initiator permits coupling to amine‐terminated poly(propylene glycol) (PPG), yielding an effective macroinitiator for synthesizing a doubly thermo‐responsive block copolymer of PPG‐block‐P(DMAEMA/2VP). A detailed study of the thermo‐ and pH‐sensitivities of the statistical and block copolymers is also presented. The cloud point temperature of the statistical copolymers is fine tuned from 14 to 75 °C by varying polymer composition and pH. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012.
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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".