Synergistic Stabilization of Emulsions and Emulsion Gels with Water-Soluble Polymers and Cellulose Nanocrystals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The effect of water-soluble polymers on the properties of Pickering emulsions stabilized by cellulose nanocrystals (CNCs) was investigated. Pretreatment of CNCs with excess adsorbing polymer, hydroxyethyl cellulose (HEC) or methyl cellulose (MC), gave smaller and more stable dodecane-in-water emulsion droplets compared to either polymer or CNCs alone, i.e., synergistic stabilization. By contrast, dextran, which does not adsorb on CNCs, gave unstable emulsions, with or without CNCs. CNCs with HEC or MC produced emulsions that showed no significant creaming or phase separation over several months. Interfacial tension, quartz crystal microbalance and confocal laser scanning microscopy measurements indicate that both HEC and MC are surface active and adsorb onto CNCs. 75% of the oil–water interface is covered by CNC particles coated with HEC or MC and the remaining interface is stabilized by HEC or MC chains not bound to cellulose. Viscoelastic emulsion gels were also produced by adding excess MC to the CNC-HEC emulsions and heating above 70 °C. The thermogelation was reversible, and multiple cycles of heating/cooling did not lead to coalescence of the emulsion. This work points to broad application of CNCs with water-soluble polymers as promising green emulsion stabilizers for food, pharmaceutical, and cosmetic products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it