Understanding the Controlled Polymerization of Methyl Methacrylate with Low Concentrations of 9-(4-Vinylbenzyl)-9<i>H</i>-carbazole Comonomer by Nitroxide-Mediated Polymerization: The Pivotal Role of Reactivity Ratios
Bibliographic record
Abstract
Previously, nitroxide-mediated controlled copolymerization (NMP) of methyl methacrylate (MMA) using BlocBuilder unimolecular initiator was found to require much less controlling comonomer when using 9-(4-vinylbenzyl)-9 H -carbazole (VBK) compared to styrene (S) as a comonomer (minimum ∼1 mol % VBK versus 4.4 mol % S). Here, we explored why this was the case. Initially, the use of dimethylformamide (DMF) solvent in the copolymerization of MMA/S was studied as the MMA/VBK copolymerizations were done in DMF. The results confirmed that the increased effectiveness of VBK as a controlling comonomer was not due to the solvent or other experimental conditions. Second, the propagation rate constant k P,VBK and various ⟨ k P ⟩ MMA/VBK for MMA/VBK copolymerizations were determined using pulsed laser polymerization–size exclusion chromatography (PLP-SEC), and the dissociation rate constants k d,VBK for the VBK-BlocBuilder adduct and PVBK chains were determined using electron paramagnetic resonance (EPR) spectroscopy, showing that k d for VBK was very similar to S and ⟨ k P ⟩ MMA/VBK was very similar to k P,MMA . Finally, modeling of the system using PREDICI was done and illustrated that the difference in reactivity ratios between MMA/S and MMA/VBK was ultimately one of the major reasons for the increased control of VBK versus S. This study showed that propagation rate of the copolymerization and equilibrium constant for the dormant/active species are not the only parameters that govern controlled NMP, and the effect of reactivity ratios between the methacrylate and the controlling comonomer must also be considered for the controlled nitroxide-mediated copolymerization of methacrylate-rich mixtures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".