Effect of Sodium Citrate on the Aggregation of Bitumen Droplets
Bibliographic record
Abstract
The bitumen droplet size is a key factor affecting recovery in mined oil sand extraction. In this study, we investigate the impact of sodium citrate (Na 3 Cit), a secondary processing aid, on the bitumen droplet size after the oil sand liberation process. By developing a model mixing system, we found that Na 3 Cit facilitates the aggregation of midsized droplets of ∼50–100 μm to form larger droplet flocs of ∼500–600 μm. To unveil the underlying mechanism, we further studied the size evolution of emulsified bitumen droplets under different water chemistries using focused beam reflectance measurement and smart online particle analysis technology. The results further confirmed that Na 3 Cit can facilitate droplet aggregation; typically, an optimum dosage could be identified, above which the beneficial effect on aggregation started to decrease and eventually became detrimental. The impact of Na 3 Cit on the bitumen droplet size may be attributed to the interplay of three major factors: slime coating, surface properties, and surface forces under different water chemistries. This research indicates that larger bitumen flocs can be formed at an optimum Na 3 Cit concentration, which in turn results in a higher bitumen flotation and increased bitumen recovery.
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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 | 0.001 |
| 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) | 0.001 | 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".