Water-in-Oleogel Emulsions—From Structure Design to Functionality
Bibliographic record
Abstract
The development of water-in-oleogel (W/Og) emulsions is highlighted, with focus placed on the key properties dictating the structuring ability of both the continuous oleogelled and dispersed phases present. The gelling ability of oleogelators is distinguished by the formation of crystalline structures, polymeric strands, or tubules. Once a dispersed aqueous phase is introduced, droplet stabilization may occur via oleogelator adsorption onto the surface of the dispersed droplets, the formation of a continuous gel network, or a combination of both. Surface-active species (added or endogenous) are also required for effective W/Og aqueous phase dispersion and stabilization. Processing conditions, namely temperature-time-shear regimes, are also discussed given their important role on dispersed droplet and oleogel network formation. The effects of many factors on W/Og emulsion formation, rheology, and stability remain virtually unknown, particularly the role of dispersed droplet size, gelation, and clustering as well as the applicability of the active filler concept to foods. This review explores some of these factors and briefly mentions possible applications of W/Og emulsions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".