Combined Hydro–Solvo–Bioleaching Approach toward the Valorization of a Sulfidic Copper Mine Tailing
Bibliographic record
Abstract
Innovative and sustainable technologies are being developed to meet the demand for critical and economically important metals and to minimize and valorize the increasing quantities of industrial waste streams. This study investigates a valorization route for the recovery of copper from a copper sulfide tailing (0.4 wt % Cu). Microwave-assisted roasting was used to transform the sulfidic fraction into a sulfate fraction, which increased the solubility of copper and other heavy metals during the following leaching steps. The roasted material was leached with an ammonia solution, and the effect on the leaching efficiency of varying the ammonia concentration was investigated. Simultaneous ammoniacal leaching and solvent extraction resulted in a high leaching efficiency of copper (nearly 100%) with a high selectivity against iron (less than 1% leaching efficiency). An indirect bioleaching step with biogenic citric acid, supported by a comparative leaching using purified organic acids, was applied to further decrease the concentration of residual metals (i.e., more than 40% leaching efficiency for Mn, around 20% leaching efficiency for Zn, and 5% leaching efficiency for Cu) and simultaneously neutralizing the pH of the substrate. A standardized environmental leaching test was performed on every leaching residue to evaluate the performance of the process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".