Cellulose Nanocrystals and Methyl Cellulose as Costabilizers for Nanocomposite Latexes with Double Morphology
Bibliographic record
Abstract
Cellulose nanocrystals (CNCs) are sustainable rigid rod-shaped nanoparticles that have potential as reinforcing agents in polymer nanocomposites. CNCs can also act as Pickering stabilizers in emulsions and foams due to their amphiphilic nature. In this work, CNCs were rendered surface active through adsorption with the biopolymer methyl cellulose (MC) to produce MC-coated CNCs. MC-coated CNCs were used to stabilize the microsuspension polymerization of methyl methacrylate. Monomer conversion, latex size, and gel content were studied. The microsuspension polymerization resulted in a double morphology where poly(methyl methacrylate) (PMMA) microparticles and nanoparticles were produced simultaneously. The ratio of micro- to nanoparticles could be tuned based on the CNC:MC ratio. Most nanoparticles were attached to the microparticles offering hierarchically structured latexes, although approximately 2 wt % were free in suspension. Drying conditions could be used to control the surface roughness of the dry latex particles. This work provides a new strategy for the incorporation of CNCs into polymer latexes and the ability to control their morphology. This method could be used to produce CNC-based adhesives, toners, cosmetics, and coatings, providing a greener route compared to solvent-based polymerization while replacing synthetic surfactants with CNCs and MC which are derived from renewable resources.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".