Tailoring Cellulose Nanocrystal and Surfactant Behavior in Miniemulsion Polymerization
Bibliographic record
Abstract
Cellulose nanocrystals (CNCs) combined with surfactants were used to stabilize miniemulsion polymerization reactions. Anionic CNCs with H + and Na + counterions and cationic-modified CNCs were investigated with anionic and cationic surfactants. When oppositely charged CNCs and surfactants were mixed, CNC size increased and absolute zeta-potential decreased, indicating surfactant adsorption and the ability to costabilize the monomer/water interface. Colloid-probe atomic force microscopy showed that surfactant adsorption to CNCs is strongly dependent on the CNC surface charge and counterion. Miniemulsion polymerization of poly(methyl methacrylate) (PMMA) was performed in the presence of CNC–surfactant mixtures; latexes were produced giving PMMA nano particles when there was no interaction between CNCs and surfactant and PMMA micro particles when CNCs and surfactant acted as costabilizers. This shows that CNCs can be used with surfactants to stabilize miniemulsion polymerization, reducing the need for a hydrophobe and leading to latexes with tunable properties (size, size distribution, surface charge, and polymer molecular weight) for coatings, adhesives, and household/personal care products.
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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) | 0.000 | 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".