Study on the effect of collector and inhibitor acid on the floatability of collophane and dolomite in acidic media by TOF‐SIMS and XPS
Bibliographic record
Abstract
Most of the phosphate ore in southern China is contained within siliceous dolomite phosphate rock, and more than 90% of it is medium and low‐grade collophane. Reverse flotation of carbonate gangue minerals (dolomite) from phosphate in acidic media is still the most economical method for the reduction of carbonate in collophane concentrates. It has been recognized that the collophane and dolomite in acidic media affect the surface properties of minerals, thereby affecting their flotation properties. In this paper, HCl and H 3 PO 4 were used as regulators or inhibitors to study the flotation behaviour of collophane and dolomite. The inhibition mechanism of collophane and dolomite in two acid media was studied by time‐of‐flight secondary ion mass spectrometry (TOF‐SIMS) and X‐ray photoelectron spectroscopy (XPS) analyses. It was found that the addition of an inhibiting acid can partially depress the collophane and improve the flotation of dolomite, thus achieving their flotation separation, and the inhibition effect of H 3 PO 4 on collophane is better than that of HCl. And it was found by TOF‐SIMS analysis that the increase in acid concentration did not reduce the adsorption concentration of the collector, and the main reason for the inhibition was not the decrease in the adsorption concentration of the collector. The adsorption capacity of collector on dolomite surface with H 3 PO 4 is greater than that with HCl. The XPS test indicated that metaphosphate (PO 3 −1 ) is the pivotal ion for depressing collophane under acid conditions.
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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) | 0.001 | 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".