Polyacrylamides revisited: flocculation of kaolin suspensions and mature fine tailings
Bibliographic record
Abstract
A series of acrylamide‐based water‐soluble (co)polymers was synthesized and they were investigated as flocculants of model kaolin suspensions and mature fine tailings of oil sands. The effects of molar mass, charge density, and polymer concentration on flocculation efficiency were studied by monitoring the initial settling rate during sedimentation. Hydrolyzed polyacrylamide (HPAM) with high molar mass and intermediate acrylic acid contents (0.14–0.41 mol/mol (14–41 mol%)) performed better in flocculation tests on kaolin suspensions requiring lower dose for maximum initial settling rate than native polyacrylamide (PAM). Surface force measurements showed that at low polymer concentrations (1 ppm), the partially‐adsorbed polymer induced a bridging attraction between the mica surfaces. Increasing the polymer concentration to 10 and 50 ppm caused purely repulsive forces. The presence of anionic groups in HPAM led to stronger repulsion, which was also demonstrated by the higher viscosity and larger hydrodynamic radius of the charged polymer. The charge‐induced increase in the viscosity of polymer solutions was suppressed by the screening effect of salts in a buffer solution and reducing the viscosity is desirable in the injection of flocculants in the industrial process.
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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".