Dried and Redispersible Cellulose Nanocrystal Pickering Emulsions
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 tannic acid (TA) and water-soluble cellulose derivatives on the properties of Pickering emulsions stabilized by cellulose nanocrystals (CNCs) was investigated. The potential to both fully dry CNC-stabilized emulsions and to redisperse the dried emulsions in water is demonstrated. When CNCs are mixed with excess adsorbing polymer, either methyl cellulose or hydroxyethyl cellulose, followed by emulsification with corn oil, oil-in-water emulsions can be transformed without oil leakage into solid dry emulsions via freeze-drying. However, these dry emulsions exhibit droplet coalescence within the solid matrix and thus cannot be redispersed. Addition of TA (after emulsification) imparts dispersibility to the dried emulsions due to complexation between the cellulose derivatives and TA which condenses the "shell" around the oil droplets. When dried emulsions with TA are placed in water, the emulsion droplets redisperse readily without the need for high energy mixing, and minimal change in emulsion droplet size is observed by Mastersizer and confocal microscopy. Therefore, the simple addition of two sustainable components to CNC Pickering emulsions (i.e., TA and methyl cellulose or hydroxyethyl cellulose) has led to the first dried and redispersible CNC-based emulsions with oil content as high as 94 wt %. These processing abilities will likely extend the use of these surfactant-free, "green", and potentially edible emulsions to new food, cosmetic, and pharmaceutical applications.
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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