Influence of Structural Variations of Demulsifiers on their Performance
Bibliographic record
Abstract
Chemical demulsification is the most widely used method for breaking water-in-diluted bitumen emulsions in oil sands processing. In this work, the properties and performance of six samples of ethylene oxide (EO)—propylene oxide (PO) block copolymer demulsifiers from two families were investigated. The demulsifiers were characterized by their relative solubility number (RSN), EO content, PO content, and molecular weight (MW). The results showed that the performance of the demulsifiers is correlated to the starting base compound, EO content, PO content, RSN, MW, degree of cross-linking, interfacial tension (IFT), yield stress of underflow, and bitumen loss. Demulsifiers with higher MW and more EO–PO branching had higher dehydration efficiencies when the EO content was varied from 0% to 40% at constant PO content. An increase in MW by cross-linking EO–PO copolymers improved the dehydration efficiency. In this work, an appropriate rheological method was developed to correlate the properties of the demulsifiers with the properties of the underflow. The yield stress of the underflow, including settled solids, water, and the rag layer, increased with increasing RSN value and dosage of demulsifier. At high dosages, the yield stress values were high because of an increased number of aggregates, which, in turn, restricted underflow. An increase in the RSN value of the demulsifiers led to more bitumen loss to the underflow, which increased the size of the aggregates present in the underflow, resulting in increased immobility and constriction and higher yield stress.
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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) | 0.000 | 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".