Vinyl phenylboronic acid controlling co‐monomer for nitroxide mediated synthesis of thermoresponsive poly(2‐<scp><i>N</i></scp> morpholinoethyl methacrylate)
Bibliographic record
Abstract
ABSTRACT Low concentrations of 4‐vinylphenylboronic acid (VPBA) were copolymerized with 2‐N‐morpholinoethyl methacrylate (MEMA) by nitroxide mediated polymerization using BlocBuilder™ unimolecular initiator at 80 to 90 °C. The MEMA/VPBA copolymerizations were performed at initial feed compositions (fVPBA,0) of 0.05 to 0.10 VPBA, with fVPBA,0 = 0.10 using dimethylacetamide (DMAc) solvent being most effective, as seen by a linear increase in number average molecular weight, Mn, versus conversion and low dispersity, Đ < 1.40. The copolymers were further chain‐extended with a second batch of VPBA, resulting in a block copolymer with monomodal molecular weight distribution and Đ = 1.66. For MEMA/VPBA copolymers, increases in VPBA composition and polymer solution concentration resulted in decreases in the cloud point temperature (CPT, typically varied between 27.4–37.8 °C) and CPT increased from 31.2 to 33.8 °C to about 88 °C with decreases in pH from 7 to 4. Rheological tests with small angle light scattering (SALS) confirmed CPTs measured by UV‐Vis and DLS. These copolymers were targeted as models to combine possible glucose‐sensing boronic acid functionality the thermoresponsiveness provided by MEMA groups. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016, 54, 1560–1572
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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".