Poly(<i>tert</i>-butyl methacrylate/styrene) Macroinitiators as Precursors for Organo- and Water-Soluble Functional Copolymers Using Nitroxide-Mediated Controlled Radical Polymerization
Bibliographic record
Abstract
Styrene/ tert -butyl methacrylate (S/TBMA) mixtures, with initial TBMA molar feed compositions f TBMA,0 = 0.1−0.92, were copolymerized by nitroxide-mediated polymerization (NMP) in bulk at 90 °C using 10 mol % { tert -butyl[1-(diethoxyphosphoryl)-2,2-dimethylpropyl]amino} nitroxide (SG1) relative to 2-({ tert -butyl[1-(diethoxyphosphoryl)-2,2-dimethylpropyl]amino}oxy)-2-methylpropionic acid unimolecular initiator (BlocBuilder) to form SG1-terminated macroinitiators. k p K values ( k p = propagation rate constant, K = equilibrium constant) for S/TBMA increased significantly as f TBMA,0 increased, with k p K = (7.4 ± 0.03) × 10 −7 to (5.4 ± 0.9) × 10 −5 s −1 . Copolymer reactivity ratios were r TBMA = 0.13−0.27 and r S = 0.43−0.59 using Fineman−Ross, Kelen−Tüdos, and nonlinear least-squares fitting to the Mayo−Lewis terminal model. All S/TBMA copolymers (number-average molecular weight M̅ n = 4.5−15.6 kg mol −1 ) exhibited low polydispersities ( M̅ w / M̅ n ≤ 1.30), and M̅ n exhibited linear behavior with conversion up to 25−40% and monomodal molecular weight distributions. TBMA-rich copolymer ( M̅ n = 14.2 kg mol −1 and M̅ w / M̅ n = 1.30) was shown to have a high degree of “livingness” based upon 31 P NMR measurements for the SG1 end group (≈75%), and successful reinitiations of fresh batches of styrene, tert -butylstyrene, N -isopropylacrylamide, and a ternary mixture of glycidyl methacrylate/methyl methacrylate/styrene (all products were monomodal with M̅ n = 17.8−81.0 kg mol −1 and M̅ w / M̅ n = 1.33−1.59).
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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".