Surface charge characterization and flotation of an ultramafic nickel ore
Bibliographic record
Abstract
About 300 million tonnes of inferred Ni resource in ultramafic hosted rocks is present in 'Thompson Nickel Belt' in north central Manitoba. The processing challenges result from electrostatic interaction between pentlandite (the main Ni-mineral) and serpentine (the main gangue and one of the MgO minerals). As a contribution to meeting the challenge, the thesis examines the role of particle and bubble surface charge and the effect of fibre disintegration on flotation behavior of an ultramafic Ni ore sample. For surface charge characterization the sedimentation potential technique was used. A novel integrated device was developed to measure sedimentation potential, conductivity and pH simultaneously. Maxwell's model was used to calculate volume fraction of dispersed phase from conductivity, and zeta potential, when appropriate, was calculated from the Smoluchowski equation. The technique was validated by showing good agreement with iso-electric point for alumina, silica and bubble suspensions with electrophoresis measurements. The technique was extended to characterize mixed minerals including ultramafic ore, and bubbles in the presence of particles. The results provided some evidence of metal ion adsorption on particles and the possibility of non-hydrophobic particle attachment to bubbles. The latter was reinforced by visualization studies of a pendant bubble exposed to particle suspensions.A novel fibre disintegration strategy was devised combining both chemical (acid) and physical (grinding) treatment based on work to enhance carbon dioxide uptake by serpentine. Using HCl, subsequent conventional flotation (amyl xanthate, soda ash and MIBC) gave significantly improved results over the untreated ore. Using H2SO4, arguably the practical option led to flotation without collector due to elemental sulphur formation on pentlandite, and without frother due to high ionic strength solutions. Improved Ni grade-recovery with higher MgO mineral rejection was achieved. Structural changes in the fibres were followed using various spectroscopic techniques and a mechanism of fibre disintegration suggested.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".