Evaluation of a Novel Polymeric Flocculant for Enhanced Water Recovery of Mature Fine Tailings
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
The novel cationic flocculant, poly(lactic acid) choline iodide ester methacrylate (poly(PLA4ChMA)), has been shown to provide improved flocculation of 5.0 wt.% mature fine tailings (MFT) diluted in deionized water compared to commercial anionic polymers, with continued dewatering of the sediment occurring as the polymer undergoes partial hydrolytic degradation. However, the elevated dosages (10,000 ppm) required would make the polymer costly to implement on an industrial scale. With this motivation, the impact of MFT loading and the use of process water is explored while comparing the settling performance of poly(PLA4ChMA) to available commercial alternatives such as anionic FLOPAM A3338. Improved consolidation of 5.0 wt.% MFT diluted with process water could be achieved at reduced dosages (500 ppm) with poly(PLA4ChMA). However, the final compaction levels after polymer degradation were similar to those achieved with the nondegradable commercial flocculants. Flocculation-filtration experiments with undiluted MFT are also conducted to compare the performance of the polymers. Significantly faster rates of water release were observed with the cationic flocculants compared to FLOPAM A3338, but no improvement in the overall tailings compaction was found either before or after poly(PLA4ChMA) degradation. Thus, the improved dewatering observed with poly(PLA4ChMA) in dilute MFT suspensions does not extend to conditions that would be encountered in the field.
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) | 0.001 | 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 it