Nitroxide Mediated Radical Emulsion Polymerization: Mathematical Modeling
Bibliographic record
Abstract
Several mathematical models for nitroxide mediated polymerization (NMP) in miniemulsion have been reported, but virtually none for nitroxide mediated polymerization (NMP) in true emulsion polymerization; in part this is due to the scarcity of processes for performing NMP in this type of aqueous dispersions. Our group has recently developed a robust NMP emulsion semibatch process which is applicable to a variety of monomers and nitroxides. In this paper, the progress made in our group in the development of mathematical models aimed at explaining the experimental effects observed in the NMP emulsion process is presented. The modeling approach is based on population balances that describe the number of particles having a specific number of active radicals and a given concentration or number of nitroxide radicals. The partitioning of the nitroxide radical and its corresponding alkoxyamines between the organic and aqueous phases is included in the model. The approach and assumptions chosen are compared with those used in other models for NMP in aqueous dispersions. The model is used as a tool to understand the quantitative effects of the main variables on the process outputs; it can also be used for scaling‐up purposes. Preliminary simulation results are presented and discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".