Solids-Stabilized Emulsions: A Review
Bibliographic record
Abstract
Introduction An emulsion is a system of dispersed droplets of one immiscible liquid in another. Simple emulsions are either oil-in-water (o/w) or water-in-oil (w/o). Emulsions can be defined as colloidal systems, although emulsion droplets are usually larger than the range specified for a colloidal system, i.e. diameter > 1 μm. Emulsions are encountered in many industries and scientific disciplines. Multidisciplinary study is required for a better understanding of emulsion behaviour and better control over industrial emulsions. In this review, solids-stabilized emulsions are reviewed and they are defined as an emulsion that is stabilized by fine solid particles. Some finely divided solids assist in the emulsion formation, and/or improve its stability. These types of emulsions have widespread applications in industrial settings and have a history of being studied, dating back to 1903. Objective of review Over the last decade, solids-stabilized emulsion experimentations are becoming increasingly more sophisticated and focused on microscopic level understanding. Some recent work has been performed to study the structure of particles at the droplet interfaces. In this review we will summarize important experimental and theoretical studies related to solids-stabilized emulsions. Considering the vast literature on solids-stabilized emulsions, this review aims at a selective, not comprehensive, overview of the progress in the field, with emphasis on key factors affecting the stability of solids-stabilized emulsions and the structure of emulsion drop interfaces.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".