Model Studies of Nitroxide‐Mediated Styrene Miniemulsion Polymerization – Opportunities for Process Improvement
Bibliographic record
Abstract
Abstract Modeling studies were performed to investigate how persulfate‐initiated nitroxide‐mediated styrene miniemulsion polymerizations are influenced by changes to the polymerization recipe. By manipulating the initial concentrations of potassium persulfate and nitroxide, and the aqueous phase volume, trends in the predicted polymerization time, number average molecular weight, polydispersity and degree of polymer livingness were identified that indicate operating conditions for improved process performance. Specifically, our model predicts the existence of experimental conditions that simultaneously minimize polymer polydispersity and maximize the livingness of the polymer. The mechanisms responsible for the predicted trends were identified from the predicted molecular weight distributions of the living and dead polymer chains. Predicted number MWDs at 20% monomer conversion for styrene NMMP systems employing various levels of [KPS]aq,0. Dormant KPS‐initiated polymer radicals. image Predicted number MWDs at 20% monomer conversion for styrene NMMP systems employing various levels of [KPS]aq,0. Dormant KPS‐initiated polymer radicals.
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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".