Monodisperse Micrometer-Size Carboxyl-Functionalized Polystyrene Particles Obtained by Two-Stage Dispersion Polymerization
Bibliographic record
Abstract
Monodisperse carboxylated micrometer-sized polystyrene particles were synthesized by dispersion polymerization of styrene in ethanol and in 95% ethanol−water in the presence of acrylic acid (AA) as a functional comonomer. When AA was present at the onset of the reaction, the resulting particles had an increased particle size and a broader size distribution than those prepared in the absence of AA. If, however, the addition of AA was delayed ca. 1 h, so that the particle nucleation stage was complete, then 2 wt % AA, dissolved in monomer plus solvent, could be added to the reaction without a deleterious effect on particle formation. When larger amounts of AA (e.g., 4 wt % based on styrene) were added, most resulting particles became unstable and coagulated if PVP55 ( M w ≈ 55000) was used as the stabilizer. Some evidence points to interaction between −COOH groups on the particles as the origin of particle aggregation. Improved colloidal stability was achieved by decreasing the solids content, increasing the polarity of the medium, and switching to PVP360 ( M w ≈ 360000) as the polymeric stabilizer. Coagulum-free particles with a very narrow size distribution containing 2%, 4%, and 6 wt % AA could be obtained in this way. Under these conditions, adding different amounts of AA in the particle growth stage did not change the particle size or size distribution.
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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) | 0.001 | 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 | 0.001 | 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".