Characterization of a hybrid polyacrylamide and its flocculation properties in cyanide tailing suspensions
Bibliographic record
Abstract
Abstract An inorganic-organic hybrid flocculant Al(OH)3-polyacrylamide (Al-PAM) with narrow molecular weight distribution was synthesized using inverse microemulsion polymerization. The hybrid polymer Al-PAM was characterized by Infrared spectroscopy, thermogravimetric analysis, transmission electron microscopy and scanning electron microscopy, and it was found that it had a ‘star-like’ structure in which Al(OH)3 colloidal particles acted as cores linking PAM chains. The properties of Al-PAM were investigated in flocculating 10 wt% cyanide tailing suspensions. It was found that as the amount of Al-PAMM1 with high molecular weight and aluminum content increased, the initial settling rate of particles accelerated, achieving the maximum 6.6 m/h, 17.3 times the rate of the control without flocculants. The turbidity of the supernatant decreased to 35 ± 2 NTU accordingly, compared to 353 ± 2 NTU of that in the control, which meant that 90.0% of turbidity was removed from the cyanide tailing suspensions. The flocculation mechanism was further explored by floccule size and ζ potential measurements. The superior performance of cationic Al-PAM in flocculating negatively charged particles compared to commercial non-ionic GG indicated that electrostatic repulsion between tailing particles was a crucial factor in deciding the flocculation performance of the polymer. The study demonstrated that both charge neutralization and bridge adsorption were conductive to the particle flocculation.
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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".