A New Method for the Preparation of Concentrated Translucent Polymer Nanolatexes from Emulsion Polymerization
Bibliographic record
Abstract
A novel method for the preparation of concentrated, colloidally stable, translucent polymer nanolatexes is presented. Herein nanolatexes are obtained from emulsion polymerization, utilizing the potential of catalytic chain transfer to enhance the particle nucleation efficiency. Low amounts of emulsifier are required (<8% w/w based on monomer) while the nanolatexes concentration can be increased to 40% w/w. The nanolatexes are translucent in appearance, which was correlated to the average particle size and width of the particle size distribution using Mie theory. Increasing the nanolatex concentration was found to have no deteriorating effect on either the optical or colloidal properties. Preparing translucent nanolatexes via this method is advantageous, as the amount of emulsifier is significantly reduced without sacrificing the optical transparency or the high interfacial surface area of the polymer colloids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".