Investigation of the formation mechanisms in high internal phase Pickering emulsions stabilized by cellulose nanocrystals
Bibliographic record
Abstract
Medium and high internal phase Pickering emulsions stabilized by cellulose nanocrystals (CNCs) have been prepared and the effects of CNC concentration and type of oil phase on the properties of emulsions were studied. The maximum oil phase volume that can be stabilized by CNCs is 87% when the CNC concentration is 0.6 wt.%; this slightly decreases to 83% when the CNC concentration is increased to 1.2 wt.% or higher. In addition, the oil droplets stabilized with 0.6 wt.% CNC suspensions have a larger size than those stabilized with higher concentration CNC suspensions. As evidenced by the change in oil droplet morphology and size, two different emulsion formation mechanisms are proposed. For a CNC concentration of 0.6 wt.%, the extra oil added into the emulsion is accommodated by the expansion of oil droplet size, whereas for CNC concentrations of 1.2 wt.% and higher, the oil is stabilized mainly by the formation of new oil droplets.
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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) | 0.000 | 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 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".