Dual Responsive Pickering Emulsion Stabilized by Poly[2-(dimethylamino)ethyl methacrylate] Grafted Cellulose Nanocrystals
Bibliographic record
Abstract
A weak polyelectrolyte, poly[2-(dimethylamino)ethyl methacrylate] (PDMAEMA), was grafted onto the surface of cellulose nanocrystals via free radical polymerization. The resultant suspension of PDMAEMA-grafted-cellulose nanocrystals (PDMAEMA-g-CNC) possessed pH-responsive properties. The grafting was confirmed by FTIR, potentiometric titration, elementary analysis, and thermogravimetric analysis (TGA); the surface and interfacial properties of the modified particles were characterized by surface tensiometer. Compared to pristine cellulose nanocrystals, modified CNC significantly reduced the surface and interfacial tensions. Stable heptane-in-water and toluene-in-water emulsions were prepared with PDMAEMA-g-CNC. Various factors, such as polarity of solvents, concentration of particles, electrolytes, and pH, on the properties of the emulsions were investigated. Using Nile Red as a florescence probe, the stability of the emulsions as a function of pH and temperature was elucidated. It was deduced that PDMAEMA chains promoted the stability of emulsion droplets and their chain conformation varied with pH and temperature to trigger the emulsification and demulsification of oil droplets. Interestingly, for heptane system, the macroscopic colors varied depending on the pH condition, while the color of the toluene system remained the same. Reversible emulsion systems that responded to pH were observed and a thermoresponsive Pickering emulsion system was demonstrated.
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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".