High‐Molecular‐Weight Poly(<i>tert</i>‐butyl acrylate) by Nitroxide‐Mediated Polymerization: Effect of Chain Transfer to Solvent
Bibliographic record
Abstract
Abstract Tert‐Butyl acrylate (TBA) was polymerized by nitroxide‐mediated polymerization (NMP) using BlocBuilder initiator and 4.5 mol‐% additional SG1 (N‐tert‐butyl‐N‐[1‐diethylphosphono‐(2,2‐dimethylpropyl)] nitroxide) relative to BlocBuilder (2‐methyl‐2‐[N‐tert‐butyl‐N‐(diethoxylphosphoryl‐2,2‐(dimethylpropyl)aminooxy]propionic acid) at 115 °C in bulk and in various solvents. In all cases, number average molecular weight ($\overline M _{\rm n}$ ) increased linearly up to 35% conversion. kpK values (kp = propagation rate constant, K = equilibrium constant) for TBA agreed well with literature data. For higher target $\overline M _{\rm n}$ > 50 kg · mol−1, solution polymerizations used to reduce viscosity were problematic as chain transfer reactions became noticeable, particularly when block copolymers with styrene were desired. A better strategy to obtain high $\overline M _{\rm n}$ block copolymers involved a semi‐batch feeding in bulk of styrene monomer to a poly(TBA) macroinitiator which resulted in high $\overline M _{\rm n}$ gradient blocks with low polydispersity ($\overline M _{\rm n}$ = 54.7 kg · mol−1, $\overline M _{\rm w} /\overline M _{\rm n}$ = 1.3). magnified image
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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) | 0.001 | 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".