Bibliographic record
Abstract
Enargite (Cu₃AsS₄) is a refractory mineral that has not been investigated extensively with respect to copper leaching. The two main challenges to its leaching is its very refractory nature, which some sources consider to be more refractory than chalcopyrite; and the mineral contains arsenic, and possibly small amounts of antimony, which will pose a challenge for the processing and the ultimate disposal of these elements. Initially, the leaching of enargite as discussed in the literature has been reviewed. It was found that the information on the leaching of enargite is sparse, and the research that has been conducted indicates that enargite is not viable to leaching. The purpose of the current work is to determine the leachability of enargite, concentrating on the bioleaching aspects. In this respect, mesophiles, moderate thermophiles, and extreme thermophiles were used at their respective temperatures using various pulp densities (19, 33, 48 and 95 g/L) and particle sizes (nominal P[sub 80] sizes of 10, 15, and 37 microns). Under these experimental conditions, it was determined that almost complete extraction of copper could be achieved using extreme thermophiles, with low pulp densities and smaller particle sizes. For the mesophiles, the decrease in particle size caused a small increase in copper extraction than that reported in the literature. Other important observations have been noted: in the mesophile and moderate thermophile leach solutions, it is very clear that pyrite is being leached preferentially to the enargite and the iron is reporting to solution. In the extreme thermophiles, however, the iron is reporting to the solid residue, possibly as a precipitate. More work will be needed to determine the viability of bioleaching enargite in a commercial process. Furthermore, many other methods by which enargite may potentially be leached have yet to be explored. For instance, chloride leaching or sulphate leaching using finer grinds and a variety of conditions may need to be considered in the future.
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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".