Liquid-Liquid Equilibrium Studies of Carbon Dioxide/Bitumen System and Utilizing Ethyl Acetate as a Co-Solvent
Bibliographic record
Abstract
Abstract In situ bitumen extraction from oil sands using thermal recovery processes has faced challenges due to reliance on steam. Additionally, the produced bitumen is highly viscous and needs to be diluted with lighter hydrocarbon products, such as field condensates, for pipeline transportation. Therefore, exploring less energy-intensive options to produce and transport bitumen economically with less environmental impact is essential. This work aimed to study the liquid-liquid equilibrium (LLE) of CO2 and bitumen at ambient temperature. First, the impact of CO2 feed mass fraction and pressure on equilibrium mixture properties are investigated. In the next step, the effect of ethyl acetate (EA) as an additive on the equilibrium properties of the mixture is studied. The equilibrium properties of the mixtures, including CO2 solubility in the heavy liquid phase, the viscosity of the heavy liquid phase, and the densities of light and heavy liquid phases, are reported. The results suggest that the viscosity of bitumen is considerably reduced by mixing it with liquid CO2 at ambient temperature. It was also shown that the bitumen viscosity could be further reduced by the addition of ethyl acetate as a co-solvent.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".