Ionic Liquids-Based\nBitumen Extraction: Enabling Recovery\nwith Environmental Footprint Comparable to Conventional Oil
Bibliographic record
Abstract
A nonaqueous process was developed using ionic liquids\n(ILs) to\nextract bitumen from Alberta oil sands at room temperature. Based\non an IL design platform of balancing lipophilic/hydrophilic properties\nwith possible interfacial interactions, trialkylamine/fatty acid-based\nILs were studied and down-selected considering performance, cost,\ncomposition, and interaction with water. The use of protic ILs also\nallowed modifying the amine/acid composition to increase the bitumen\nextracted and decrease the solid content in extracted bitumen. Using\nthe IL trioctylammonium oleate ([HN<sub>888</sub>][Oleate]) at a 1:3\nIL/oil sand mass ratio, we were able to achieve bitumen extraction\nfrom high-grade Alberta oil sands of ca. 100% with low solids content\n(<1%) in a fast, low-energy process. Our results demonstrate that\nthe proper design of the IL can lead to efficient oil extraction without\nconventional solvents, without generating aqueous tailings, and with\nminimum energy consumption, that is, a production process with environmental\nimpacts comparable to those associated with production of other hydrocarbon\nresources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.333 | 0.011 |
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; both teacher heads agree on what is shown here.
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".