Study on the surface chemistry behavior of pyrochlore during froth flotation
Bibliographic record
Abstract
Separation of pyrochlore from its associated minerals is typically accomplished by froth flotation. The surface chemistry of pyrochlore is similar to many of its associated non-value minerals. Therefore, understanding the surface chemical properties of the pyrochlore for selective pyrochlore flotation will potentially aid in the design of flotation strategies for optimized recovery. In this study, pyrochlore samples were collected from various points in the flotation scheme at the Niobec plant, Quebec, Canada. The SEM-EDX analysis revealed that pyrochlore from the Niobec deposit occurs as high and low iron varieties, and that recovery favours varieties with a lower Fe content. To understand a potential relationship between pyrochlore matrix composition and the related effect on collector adsorption, the surface of grains from the concentrate and tails were examined by TOF-SIMS. The surface analyses of different pyrochlore grains showed that species indicative of the cationic collector (Tallow diamine acetate) favour Fe poor pyrochlore relative to the Fe rich variety. XPS was used to analyse the surface of high Fe and low Fe pyrochlore in order to identify a potential relationship between pyrochlore matrix composition and surface chemistry. The XPS results verified a relationship between pryochlore surface oxidation and Fe content in the mineral matrix; high Fe pyrochlore particles showed a greater proportion of surface oxidation species suggesting preferential oxidation in comparison with low Fe pyrochlore particles. SEM-EDX analyses revealed that many of the pyrochlore grains were compositionally zoned into regions of high and low Fe contents. TOF-SIMS and XPS analyses were used to analyse the surface of the compositionally zoned Fe pyrochlore grains, in order to link collector adsorption to Fe contents and identify potential mechanisms for the partitioning. Surface analyses of conditioned pyrochlore grains showing zones of high and low Fe content revealed that species indicative of the collector favour the regions with low iron. XPS analyses of similarly treated compositionally zoned pyrochlore grains showed that a greater proportion of surface oxidation species corresponded to the zones with high matrix Fe content. These results are in accord with the results identified for non zoned pyrochlore grains of variable matrix Fe content and verifies the link between pyrochlore Fe composition, surface oxidation and, area selective collector loading.
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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".