Designing catechol‐end functionalized poly(DMAm‐<i>co</i>‐NIPAM) by RAFT with tunable LCSTs
Bibliographic record
Abstract
ABSTRACT Providing catechol‐end functionality to controlled structure lower critical solution temperature (LCST) copolymers is attractive, given the versatility of catechol chemistry for tethering to nanostructures. Controlled polymer chain lengths with catechol RAFT end groups are of interest to provide tunable LCST behavior to nanoparticles, although these polymerizations are relatively unexplored. Herein, the reactivity ratios for the RAFT copolymerization of N,N‐dimethylacrylamide (DMAm) and N‐isopropylacrylamide (NIPAM) pairs based on catechol‐end RAFT agents using an in situ NMR technique were first determined. Several catechol‐end poly(DMAm‐co‐NIPAM) samples were then prepared using the RAFT agent to provide copolymer. The reactivity ratios for the DMAm‐NIPAM pair were rDMAm = 1.28–1.31 and rNIPAM = 0.48–0.51. All the poly(DMAm‐co‐NIPAM) samples were found to have Mn values ≤ 26 kDa and Ð < 1.08 with LCST values ranging from 31 to 92°C, while maintaining a short range of glass transition temperature (Tg = 118–137°C). The difference in LCST values for the catechol functionalized poly(DMAm‐co‐NIPAM) based on 0.5 wt% aqueous buffered solutions at pH 5.5 and 8.5 was found to be <3.0°C. These conditions are suitable for subsequent catechol‐induced coordination and nucleophilic addition chemistry for covalent and noncovalent linkages during subsequent post‐modification. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017, 55, 4062–4070
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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 | 0.001 |
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".