Pore-Scale Analysis of Green Solvents for Solvent-Based Bitumen Recovery
Why this work is in the frame
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Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Bitumen is a critical resource for materials and energy, but its high viscosity requires energy-intensive recovery methods with significant environmental impacts. While CO 2 emissions per barrel from oil sands have decreased by 30% over two decades, further innovations are needed for sustainable extraction. We studied green solvents derived from biomass as an environmentally friendly alternative to hydrocarbons in solvent-assisted bitumen recovery. Using Hansen solubility parameters, we optimized binary solvent mixtures to enhance the solubility and minimize viscosity. A novel high-pressure microfluidic device was used to simulate reservoir conditions, verify predictions based on Hansen solubility, and evaluate recovery performance, while dynamic light scattering and elemental analyses revealed the effect of solvent composition on bitumen precipitation and solubility. In toluene/furfural and toluene/guaiacol mixtures, the particle size of dispersed species was larger than that in toluene/ethyl acetate. Moreover, heptane/ethyl acetate caused a higher precipitation of the aromatic fractions. These findings advance the understanding of green solvents for reducing the carbon footprint of bitumen recovery technologies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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 it