Role of pH on the adsorption of xanthate and dithiophosphinate onto galena
Bibliographic record
Abstract
In the concentrators of a Mexican mining company has been observed that the pH of the flotation has a significant effect on the galena recovery: the increase of pH from 7.5 to 9.5 in the Pb/Cu flotation circuit, resulted in a decrease of about 10% of lead recovery. In the present investigation, experimental models and techniques were developed to study the effect of pH on xanthate and di-isobutyl dithiophosphinate adsorption onto galena. The results obtained by UV / Vis spectroscopy showed that once galena surface has been slightly oxidised by the dissolved oxygen of the aqueous suspension, adsorption of both surfactants increases significantly, being adversely affected by the increase of pH from 5.5 to 9.5. Microflotation measurements performed for both surfactants support these findings. Thermodynamic simulation of the system suggests that the observed behaviour is due to the nature of the solid species formed on the galena surface at the particular pH: lead sulfate (PbSO4) under neutral and slightly acid conditions, and the basic sulfate (2PbO·PbSO4) under neutral and slightly alkaline conditions, as well as to their respective solubility. Infrared spectrometry confirmed the occurrence of sulfate onto galena particles, with a higher concentration for the acid pre-conditioning compared to the alkaline pre-conditioning.
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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 | 0.001 |
| 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 | 0.001 | 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".