Screening Design of Experiments of AGET ATRP of Butyl Methacrylate in a Stirred Emulsion Reactor
Bibliographic record
Abstract
Abstract This study investigates the ab initio atom transfer radical polymerization of butyl methacrylate using activator generated by electron transfer in a well‐mixed 2 L emulsion reactor. A first time reported polymerization system initiates by a catalyst complex with hexamethylenetetramine as a ligand and in presence of sodium dodecyl sulfate as an anionic surfactant. The system shows a relatively low monomer conversion rate of 14% and a controlled number average molecular weight (Mn) of 8 kg mol−1with a polydispersity index (Ð) of 1.24 for 2 h reaction time. A statistical design of experiments is followed to study the effects of reaction temperature, surfactant amount, stirring speed, and ligand amount to assess their impact on the monomer conversion,Mn, andÐ. A fractional factorial with a resolution IV design is adopted and an empirical regression model is developed from eight experimental trials. The results tell that the reaction temperature has the greatest influential on the process outputs. Also, the surfactant amount and stirring speed strongly affect the conversion rate, while the ligand amount strongly affects theMnandÐ. The results also show that the temperature–surfactant interaction is the most significant on the conversion rate andMn.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".