Role of Asphaltenes in Stabilizing Thin Liquid Emulsion Films
Bibliographic record
Abstract
Drainage kinetics, thickness, and stability of water-in-oil thin liquid emulsion films obtained from asphaltenes, heavy oil (bitumen), and deasphalted heavy oil (maltenes) diluted in toluene are studied. The results show that asphaltenes stabilize thin organic liquid films at much lower concentrations than maltenes and bitumen. The drainage of thin organic liquid films containing asphaltenes is significantly slower than the drainage of the films containing maltenes and bitumen. The films stabilized by asphaltenes are much thicker (40-90 nm) than those stabilized by maltenes (∼10 nm). Such significant variation in the film properties points to different stabilization mechanisms of thin organic liquid films. Apparent aging effects, including gradual increase of film thickness, rigidity of oil/water interface, and formation of submicrometer size aggregates, were observed for thin organic liquid films containing asphaltenes. No aging effects were observed for films containing maltenes and bitumen in toluene. The increasing stability and lower drainage dynamics of asphaltene-containing thin liquid films are attributed to specific ability of asphaltenes to self-assemble and form 3D network in the film. The characteristic length of stable films is well beyond the size of single asphaltene molecules, nanoaggregates, or even clusters of nanoaggregates reported in the literature. Buildup of such 3D structure modifies the rheological properties of the liquid film to be non-Newtonian with yield stress (gel like). Formation of such network structure appears to be responsible for the slower drainage of thin asphaltenes in toluene liquid films. The yield stress of liquid film as small as ∼10(-2) Pa is sufficient to stop the drainage before the film reaches the critical thickness at which film rupture occurs.
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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".