Total Internal Reflection Fluorescence Microscopy to Study Bitumen and Clay Interaction in Oil Sands Tailings
Bibliographic record
Abstract
Oil sands tailings management remains to be a major challenge for oil industry in Canada. Promoting quick settling of fines in tailings ponds is the key to its treatment. Bitumen lost to tailings during oil sands extraction is also believed to hinder settling and consolidation of clays in tailings ponds. Complete understanding of the factors that impede fast settling of tailings would be the ground work for development of improved tailings settling techniques and flocculants. In this study, bitumen-clay association and effect of bitumen on clay particle-particle interactions in mature fine tailings (MFT) is investigated with Total Internal Reflection Fluorescence (TIRF) microscope among other techniques. Bitumen displays natural fluorescence when illuminated with 488 nm and 543 nm. This was also established using spectrofluorometer. Fluorescence microscope imaging, ensured that clay and water did not show fluorescence. These outcomes along with high axial resolution and high contrast of TIRF were utilized to understand how bitumen interacts with clay surface in MFT. MFT sample were also diluted with process water and deionized water separately, to recognize clay boundaries under bright field microscope. The presence of hydrophobic fine clay agglomerates along with the hydrophilic clay particles was apparent from the TIRF results. Bitumen was detected to be coating clay particles and bridging clay agglomerates. By reducing the laser intensity, at laser angle above critical angle, bitumen was observed to be only partially coating some clay surfaces. The existence of biwettable clays in MFT was evident in these images. Confocal Laser scanning microscope (CLSM) which also gives high contrast images with controlled depth of field, confirmed the presence of non-uniform bitumen coating in clay surfaces. At 0.21 µm resolution, no free bitumen could be apprehended. Using He-ion microscope (HIM) which gives resolution up to 0.25 nm and high surface sensitivity, preliminary MFT images were obtained to clearly witness the layered structure of clays. Correlative studies with HIM and TIRF will pave way to realize the clay surface properties that are partially coated with bitumen.
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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 | 0.001 |
| 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".