Assessment of the impact of grinding conditions and water quality on the flotation of rare earth elements bearing minerals using hydroxamic acid
Bibliographic record
Abstract
Froth flotation is commonly used for the separation of rare earth minerals (REMs). A better understanding of flotation is of interest for REMs and non-sulfide minerals that carry other elements such as niobium and lithium. This study explores the effect of grinding conditions and water quality on the flotation performance of REMs at laboratory scale using material from the Ashram carbonatite deposit (Canada). Denver cell testing was used to evaluate how different particle sizes (P80 between 20 and 34 µm) and rod size distributions in conventional grinding impacted the performance of REM flotation using a hydroxamic acid collector (1120 g/t). The effect of water quality (i.e. presence of rust or other species) was also evaluated. REMs, mostly monazite, represented 3% of the feed material mass with dolomite as the main gangue mineral. A P80 of 24 µm strikes a compromise between sufficient liberation and limited entrainment. Grinding media corrosion negatively affected separation efficiency, causing recovery of quartz, which was possibly activated. While entrainment is responsible for over 50% of dolomite recovery, aggregation and/or slow gangue flotation account for another 40% and play an important role in achieving selectivity, highlighting the role of pulp chemistry in selective flotation of REMs.
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How this classification was reachedexpand
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) | 0.002 | 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 teacher head, 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".