Interaction Mechanism of Oil-in-Water Emulsions with Asphaltenes Determined Using Droplet Probe AFM
Bibliographic record
Abstract
Emulsions with interface-active components at the oil/water interface have long been of fundamental and practical interest in many fields. In this work, the interaction forces between two oil droplets in water in the absence/presence of asphaltenes were directly measured using droplet probe atomic force microscopy (AFM) and analyzed using a theoretical model based on Reynolds lubrication theory and the augmented Young-Laplace equation by including the effects of disjoining pressure. It was revealed that the interaction forces measured between two pristine oil droplets (i.e., toluene) could be well described by the classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, while an additional steric interaction should be included in the presence of asphaltenes in the oil. The surface interaction and the stability of oil droplets in aqueous solution were demonstrated to be significantly influenced by the asphaltenes concentration in oil, salt concentration, pH, and presence of divalent ions (Ca(2+)) in water. Adsorbed asphaltenes at the oil/water interface led to more negative surface potential of the oil/water interface and also induced steric repulsion between oil droplets, inhibiting the drop coalescence and stabilizing the oil-in-water emulsion. Lower pH of aqueous solution could lead to less negative surface potential and weaken the repulsion between oil droplets. Addition of divalent ions (Ca(2+)) was found to disrupt the protecting effects of adsorbed asphaltenes at oil/water interface and induce coalescence of oil droplets. Our results provide a useful methodology for quantifying the interaction forces and investigating the properties of asphaltenes at the oil/water interfaces and provide insights into the stabilization mechanism of oil-in-water emulsions due to asphaltenes in oil production and water treatment.
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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".