Bioflotation of sulfide minerals with <i>Acidithiobacillus ferrooxidans</i> in relation to copper activation and surface oxidation
Bibliographic record
Abstract
Surface oxidation of sulfides and copper (Cu) activation are 2 of the main processes that determine the efficiency of flotation. The present study was developed with the intention to ascertain the role of the phenomena in the biomodification of sulfides by Acidithiobacillus ferrooxidans culture (cells and growth media) and their impact in bioflotation. Surface characteristics of chalcopyrite, sphalerite, and pyrrhotite, alone and in mixtures, after interaction with A. ferrooxidans were evaluated. Chalcopyrite floatability was increased substantially by biomodification, while bacteria depressed pyrrhotite floatability, favoring separation. The results showed that elemental sulfur concentration increased because of the oxidation generated by bacterial cells, the effect is intensified by the Fe(III) left in the culture and by galvanic contact. Acidithiobacillus ferrooxidans culture affects the Cu activation of sphalerite. The implications of elemental sulfur concentration and Cu activation of sphalerite are key factors that must be considered for the future development of sulfide bioflotation processes, since the depressive effect of cells could be counteracted by elemental sulfur generation.
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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) | 0.000 | 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 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".