Phase Separation and Interfacial Viscoelasticity of Charge-Neutralized Heavy Oil Nanoemulsions in Water
Bibliographic record
Abstract
Steam-assisted gravity drainage processes for heavy oil recovery produce extremely stable nanoemulsions that remain dispersed in water for years if left untreated. The need to produce clean water for recycling demands that the nanoemulsions be destabilized and the oil phase separated from the water. The destabilization of these nanoemulsions requires an understanding of the nature of the oil−water interface. In this paper, the ζ potential and sizes of the nanoemulsions were measured with and without treatment with a cationic polymer. The coalescence of nanoemulsions was monitored by size changes using dynamic light scattering, microscopy, and water-phase separation kinetics. Small-deformation pendant drop oscillation was used to measure the dilational viscoelasticity of the oil−water interface with and without polymer adsorption. The results indicated that both the size and the large negative ζ potential contribute to the stability of the nanoemulsions in water. The addition of polymer not only causes charge neutralization but also enhances the interfacial activity and modifies the interfacial dilational viscoelasticity. The viscoelasticity is dependent on the frequency of droplet oscillation. Polymer adsorption modifies these interfacial properties while enabling coalescence and phase separation.
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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 | 0.000 |
| 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) | 0.000 | 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".