Studies on Bastnaesite Flotation: Mineral-Mineral Interactions and Selectivity Issues
Bibliographic record
Abstract
This thesis describes an experimental study on the flotation of a Canadian REE ore. The mineralogical analysis carried out indicated bastnaesite as the REE mineral containing Ce, La, Nd, and others in decreasing order of their concentrations. The focus was the examination of the separation trends of the major gangue mineralogy associated with bastnaesite. Collectors used were carboxylic types (e.g., NaOL, and veg. oil) and phosphate types (cetyl, PCP and dodecyl, DDP) and various depressants (e.g., sodium silicate, citric acid, and others). Micro-flotation techniques served to screen these reagents for their effectiveness in various combinations using both single-mineral and mixed mineral as well as batch-flotation experiments. \n \tNaOL was generally too strong for selective flotation despite using some depressants. PCP indicated promising results in micro-flotation but was not effective in batch flotation. DDP was better than PCP in batch flotation tests. Sodium silicate was effective for the depression of quartz if it was not heavily activated. TB is a soft depressant in comparison with sodium silicate. In many cases, the results that appeared to be promising according to single mineral micro-flotation tests were not effective when mixed minerals were used. Calcite exhibited a strong antagonistic effect on bastnaesite flotation with various collectors. The best results on selective separation of bastnaesite were obtained using NaOL and Sodium hexametaphosphate (SHMP) combination. SHMP consistently depressed bastnaesite in both single and mixed mineral cases, allowing for reverse flotation of calcite, which was studied in detail using the Box-Behnken method of DoE statistical analysis. \nBatch flotation tests further revealed the importance of mineral-mineral interactions, especially as induced by calcite. However, in batch tests, calcite’s interaction was not antagonistic. It induced inadvertent activation on quartz while actively participating in flotation by itself as its concentration increased in the feed. TB was found effective in the depression of quartz. DDP produced the best grade-recovery for bastnaesite in batch flotation using DI water indicating its high sensitivity to water chemistry. The findings of this study have implications for the development of selective flotation strategies for bastnaesite ores, which are important sources of rare earth elements in various industrial applications.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".