Role of sodium dodecylbenzenesulfonate in 2,2,6,6‐tetramethy‐1‐piperidinyloxy‐mediated styrene miniemulsion polymerization
Bibliographic record
Abstract
Abstract In studying 2,2,6,6‐tetramethy‐1‐piperidinyloxy (TEMPO)‐mediated styrene miniemulsions, we have observed that the surfactant sodium dodecylbenzenesulfonate (SDBS) not only provides colloidal stability but also influences the rate of polymerization. Increasing the SDBS concentration results in higher polymerization rates, although the molecular weight distribution and particle size distribution are not significantly impacted. We have also examined another common sulfonate surfactant, DOWFAX 8390. In contrast to SDBS, DOWFAX 8390 does not affect the polymerization rate. Furthermore, DOWFAX‐stabilized polymerizations are slower than SDBS‐stabilized polymerizations. TEMPO‐mediated bulk styrene polymerizations are also accelerated significantly in the presence of SDBS. Although the mechanism for the rate acceleration is unknown, the experimental evidence suggests that SDBS is participating in the generation of radicals capable of propagating, thereby reducing the TEMPO concentration within the particles. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 5974–5986, 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 | 0.000 | 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".