Studies on Bitumen−Silica Interaction in Aqueous Solutions by Atomic Force Microscopy
Bibliographic record
Abstract
The forces between spin-coated bitumen on a silica wafer and a silica particle in aqueous solutions were measured with an atomic force microscope. The effect of solution pH, salinity, divalent ion addition, and temperature on the interaction/adhesion forces was studied. The results showed that higher solution pH and temperature and lower salinity and calcium concentration resulted in a system of a stronger long-range repulsive force and a weaker adhesive force, which is favorable for bitumen detachment from the silica surface and the subsequent stabilization. The long-range interaction forces between bitumen and silica can be well described with the classical Derjaguin−Landau−Verwey−Overbeek theory, suggesting that the electrostatic forces play a dominant role in a bitumen−silica colloidal system. The best-fitted Stern potentials of bitumen and silica were in excellent agreement with the corresponding zeta potential values measured independently using an electrophoresis technique. An additional repulsive force was observed at a relatively short separation. This additional repulsion can be attributed to a polymer-like steric force. The implication of the interaction forces measured by atomic force microscopy was confirmed by zeta potential distribution measurements. The quantitative description of bitumen/silica interaction provided fundamental insights into the bitumen extraction mechanism in a water-based system for bitumen extraction from oil sands and justified the industrial use of caustics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".