Separation of bitumen from oil sands using a switchable hydrophilicity solvent
Bibliographic record
Abstract
Separation of bitumen from oil sands is far more efficient with an organic solvent than with the conventional hot water (Clark) process, but the removal of the organic solvent from the bitumen requires distillation. Distillation is problematic because of the energy cost and the need for a volatile solvent (which is therefore likely to be flammable and smog-forming). A switchable hydrophilicity solvent (SHS) is a solvent that is water-miscible in the presence of an atmosphere of CO2 but separates from water when CO2 is absent. Extraction of bitumen from low-grade high-fines oil sands using a SHS (CyNMe2) is efficient, removing 94%–97% of the bitumen. The resulting solids (sand and clay) are dry, free-flowing, and contaminated with only 0.4 wt % of bitumen and as little as 102 ppm of the solvent. No distillation step was required to recover the solvent from the bitumen. Instead, carbonated water extraction removed the solvent from the oil. Losses of the CyNMe2 solvent were, for the best method, 0.06 grams of solvent per gram of bitumen recovered. The method recovers more oil than the Clark process, produces cleaner solids, works with low-grade high-fines oil sands, and requires neither distillation nor a volatile 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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".