Interfacial Dynamics of SDS-Stabilized Hexadecane-In-Water Nanoemulsions in the Megahertz Range
Bibliographic record
Abstract
Dynamic mobility spectra of sodium dodecyl sulphate (SDS)-stabilized hexadecane nanodrops in aqueous NaCl electrolytes are measured using the electrokinetic-sonic amplitude, and interpreted using a recently proposed theory for highly charged drops with thin double layers. This novel interpretation shows that emulsion drops exhibit fluid-like dynamics at megahertz frequencies, whereas such drops have conventionally been assumed to behave as rigid spheres because of the interfacial “freezing” effects arising from interfacial Maxwell and Marangoni stresses. Our results lend support to a view of SDS-decorated emulsion drops—in the ∼100–1000 nm range—as being very highly charged, in a colloidal regime for which the standard electrokinetic model predicts two ζ-potentials for a single steady electrophoretic mobility. Although electrophoretic mobility measurements carried out with light-scattering electrophoresis are conventionally converted to a ζ-potential using the Smoluchowski formula, the present experimental and theoretical interpretations suggest that the Smoluchowski ζ-potential obtained with the Guoy–Chapman model may erroneously predict the surface charge density, perhaps explaining why—despite decades of research—it has been so challenging to reach a consensus on how to resolve electrokinetic and thermodynamic studies of SDS-decorated oil–water interfaces. The present work identifies new challenges in interpreting the electrokinetic dynamics at surfactant concentrations above the critical micelle concentration, a regime in which electrostatic screening is not well understood.
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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".