Wettability Alteration of Clay in Solid-Stabilized Emulsions
Bibliographic record
Abstract
Processing of bitumen froth obtained from surface mining process of Athabasca oil sands yields stable water-in-diluted bitumen emulsions. Even with a demulsifier, a “rag layer” forms between the oil and free water layers when clay solids are present. Experiments reveal that wettability of clay solids has a significant effect on emulsion stability. Kaolinite in toluene–brine mixture was chosen as model system to study clay wettability alteration related to emulsion separation in bitumen froth treatment. Sodium naphthenate was added to simulate the presence of naphthenic acid in diluted bitumen. The fraction of the kaolinite that settled to the bottom of the aqueous phase was measured, and was referred to as “water-wet fraction”, to characterize the wettability of kaolinite. Without any additives, 96% of the kaolinite was water-wet. Addition of only 100 ppm sodium naphthenate reduced the water-wet fraction to only 18%. Wettability of kaolinite was altered by pH control, silicate, and surfactant under different mechanisms. Addition of 366 ppm silicate at pH 10 resulted in 80% of kaolinite being water-wet. To prevent emulsion formation at high pH, cationic and amphoteric surfactants were evaluated as an alternative to alkali. Over 90% of kaolinite became water-wet when adding alkyl quaternary ammonium bromide, betaine, or amine oxide with optimal dosages.
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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".