Flocculation and Dewatering of Mature Fine Tailings Using Temperature-Responsive Cationic Polymers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Temperature-responsive copolymer with cationic charge was prepared with N-isopropylacrylamide (NIPAm) and 2-aminoethyl methacrylamide hydrochloride (AEMA) by conventional free-radical polymerization. The flocculation performance of the copolymer, poly(AEMA-st-NIPAm), was compared to five different mixture ratios of polyNIPAm and cationic poly(acrylamide-st-diallyldimethylammonium chloride) (poly(AAm-st-DADMAC)). The effects of polymer mixture ratios, polymer dosages, and temperature on solid-liquid separation as a function of initial settling rates (ISR), supernatant turbidity, sediment solid content, and water recovery were investigated. Poly(NIPAm) can facilitate particles aggregation by bridging and hydrogen bonding under lower critical solution temperature (LCST); whereas, at temperature above LCST, the adsorption of poly(NIPAm) chains on particles can be enhanced by hydrophobic interaction. A two-step (25 °C → 50 °C → 25 °C) consolidation can further enhance the sediment solid content by polyNIPAm. While the neutral property of polyNIPAm resulted in high turbidity of supernatant, mixing with poly(AAm-st-DADMAC) increases the clarity of supernatant by neutralization of fine particles. The copolymer poly(AEMA-st-NIPAm) functions as a polyelectrolyte to enhance the polymer adsorption onto particles via electrostatic interactions, thus further improving ISR and supernatant clarity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it