The development of a novel non‐leaching flocculant, derived from activated carbon and polyacrylamide
Bibliographic record
Abstract
Abstract Canadian oil sands are the third largest oil reserves in the world, containing an estimated 28.3 billion m 3 of recoverable bitumen. Extraction of bitumen via surface mining and water‐based extraction leads to the formation of tailings ponds, which contain slow settling mature fine tailings (MFT). These MFT can take hundreds of years to settle on their own. Polymer flocculants are used to improve the settling rate of the MFT. This requires a significant amount of polymer, which may itself have environmental impacts. Here, we describe development of a solid‐state flocculant using activated carbon (AC) as a backbone for polyacrylamide (PAM) flocculant branches, with the intention that this solid‐state flocculant would reduce the amount of polymer applied, replacing the bulk of the material with hydrophobic AC, and limit leaching of these materials. The development of this flocculant is achieved by bromination of AC followed by reaction with cis ‐octadecen‐1‐ol at the carbon surface. Subsequently, PAM was attached to the alkene of the enol via thermally induced radical polymerization. This AC‐PAM demonstrated effective flocculation of 5% MFTs at a minimum dosage of 120,000 ppm with an initial settling rate of 33 m/h. Thermogravimetric analysis determined that the AC‐PAM had 2% PAM content, indicating that the system only uses 2400 ppm polymer, which is a significant reduction when compared to the typical 20,000 ppm of PAM otherwise required to flocculate 5% MFTs. This demonstrates a marked reduction in the polymer required to flocculate MFTs, reducing potential environment impact.
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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) | 0.000 | 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 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".