Fine particle flotation using columns (conventional and Jameson downcomer) for a niobium deposit in Canada
Bibliographic record
Abstract
Niobium, originally called columbium, is an important element used in alloying and currently mineral from three deposits, two in Brazil and one in Canada "Niobec".The current production rates of niobium are considered sufficient to meet the global demand.However, this may not always be the case.The minerals containing the highest amount of niobium are pyrochlore and columbite.The main method for their recovery is flotation, utilized by all three processing plants.Currently, a significant amount of niobium is lost as slimes, which are removed prior to flotation due to their negative impact on the separation.This thesis is investigated the potential of recovery the "lost" niobium through flotation.The properties of valuable and gangue minerals were analyzed through microflotation, zeta potential and bench flotation.Column and Jameson cell flotation was carried out to investigate the amount of mineral that could be recovered.The collectors that were used for the analysis were: sodium oleate, florrea 7510, dodecylamine and benzohydroxamate, in the presence and absence of activating ions (cobalt and lead).On the other hand, the gangue mineral is dolomite which was analysed to understand their behaviour.The minerals showed their possible separation under each collector (different schemes).Pyrochlore presented high percentages of recovery in microflotation under the analyzed collectors and activators.These high percentages are convincing according to the results obtained from zeta potential.Columbite showed its best results at pH 7 under florrea 7510 + lead and benzohydroxamate + lead, while with dodecylamine the best recovery is obtained at pH 9 and with sodium oleate + lead at pH 5 the highest recovery is shown.Finally, dolomite indicated that low recovery percentages can be obtained with florrea 7510 + lead and benzohydroxamate + lead.Flotation of the slimes sample did not lend to a concentration of niobium in the recovered froth, which is contrary to the microflotation tests.This indicates that further research is required to iii optimize the process, this includes investigation, whether other minerals are preferentially absorbing the reagents.The inclusion of pre-concentration using other techniques targeting the physical properties could be employed.These would include the multi-gravity separator (density based) and wet high intensity magnetic separation which are effective for fine particle processing.
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.
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) | 0.000 | 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".