Iron and sulfur control during pressure leaching of sulfide concentrates in the presence of chloride ions at 150°C
Bibliographic record
Abstract
TECK and Vale operate their medium temperature copper and nickel sulfide concentrate leaching processes at 150°C. “Medium temperature” is used to describe a variety of processes that operate above the melting point of sulfur (119°C) but below the temperature where sulfur become highly viscous (159°C). During leaching, and depending upon various process parameters, iron (Fe) may precipitate as hematite, goethite, jarosite or other oxyhydroxide compounds. Hematite is the favored precipitate because it is the most environmentally (thermodynamically) stable and does not ad/absorb as much copper (Cu), nickel (Ni), or other solution constituents during precipitation. A better understanding of the formation and structure of these iron precipitates may elucidate key factors that would ultimately result in lower valuable metal losses and more stable leach residues. This thesis details the experimental work performed to clarify the conditions under which the precipitation of highly crystalline hematite occurs during medium temperature leaching of copper sulfide concentrates. Various process parameters at the lab scale were studied and classical, as well as newly developed, methods to identify the optimal conditions for hematite precipitation were employed. Higher acid concentrations resulted in increased copper extractions and favor the formation of hematite during concentrate leaching, rather than other metastable phases. Seeding with synthetic hematite resulted in more crystalline residues. Furthermore, commercially available water displacement formula ‘WD40®’ and other novel reagents (benzene sulfonic acid, phenyl phosphonic acid, decane, mineral oil) affect Fe precipitation and sulfur chemistry, leading to very different process outcomes such as improved extractions (from 98.0 to 99.2%) and larger, more easily separated, sulfur particles (from 20 µm to 1 mm). The solubility of ferrihydrite (and its main transformation product, hematite) increased with increasing acid concentration. The solid-state transformation of ferrihydrite to hematite was found to be the major mechanism. These results indicate that the ferrihydrite formed in the CESL process will eventually transform into hematite, but that solution potential will play an important role in the nature of iron oxide residue. Ferrihydrite transformation was not complete within the time (60 min) that is typically used in medium temperature leaching for the simple system studied here.
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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".