Charge–Dipole Attraction as a Surface Interaction between Water Droplets Immersed in Organic Phases
Bibliographic record
Abstract
The dynamic behavior of emulsion droplets during their interactions with one another or with solid surfaces plays a paramount role in their ultimate stability in various applications. While the interaction of oil droplets through a surrounding aqueous phase is well understood, recent studies on the interaction of water droplets through a surrounding pure organic phase showed the presence of an unexplained attraction between water droplets at relatively long ranges. In this research study, we propose fixed-surface-charge-bulk-dipole attraction as a new interaction force between water-in-oil droplets and then derive an equation for its disjoining pressure. The behavior of water droplets in the presence and absence of this charge-dipole interaction was numerically quantified using the Stokes-Reynolds-Young-Laplace model and compared to the experimental data. Numerically calculated net force curves are in excellent agreement with experimental data from the literature when charge-dipole attraction is included, while they deviate in its absence. In addition, the water droplet and thin oil film profiles in the presence and absence of charge-dipole attraction were calculated and compared. This research indicates that charge-dipole attraction can adequately explain the mysterious force observed in some studies, which demonstrates its unexplored potential to capture the physical properties and dynamic behavior of water droplets in organic phases with useful implications to unravel unidentified interactions between emulsion droplets in different industries.
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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) | 0.001 | 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".