Reversible‐addition fragmentation chain transfer radical emulsion polymerization by a nanoprecipitation process
Bibliographic record
Abstract
Abstract Polymerizations of styrene under emulsion reversible‐addition fragmentation chain transfer polymerization conditions are reported. Using a recently developed nanoprecipitaiton process, emulsion particles were formed by the precipitation of an acetone solution of a macroRAFT agent into an aqueous solution of poly(vinyl alcohol). The particles were then swollen with monomer and subsequently polymerized. Emulsion polymerizations were performed at 65 and 75 °C in which either KPS, BPO, or a combination of both was used as an initiating source. Reactions were also performed at temperatures over 100 °C in which the thermal initiation of styrene was used as an initiating source. In all cases, the polymerizations proceeded in a living manner, yielding polymers that showed an incremental increase in molecular weight with time and had narrow molecular weight distributions. Plots of number‐ average molecular weight versus conversion were linear, indicating a controlled polymerization. The resulting latices were colloidally stable and gave particle size distributions with a typical average particle diameter in the 150 nm range. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 5708–5718, 2006
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".