A Study of the Effect of Djurliete, Bornite and Chalcopyrite during the Dissolution of Gold with a Solution of Ammonia-Cyanide
Bibliographic record
Abstract
The high solubility of copper sulphide minerals is an issue in the cyanidation of gold ores. The objective of this study was to quantify the effect of individual copper sulphide minerals on the Hunt process, which showed advantages over cyanidation. High purity djurleite, bornite and chalcopyrite, with a P70 of 70–74 microns, were mixed with fine quartz and gold powder (3–8 micron) to obtain a copper concentration of 0.3%. The ammonia-cyanide leaching of slurry with djurleite proved to be more effective than cyanidation; producing comparable extraction of gold (99%), while reducing the cyanide consumption from 5.8 to 1.2 kg/t NaCN. Lead nitrate improved the Hunt leaching. The lower cyanide consumption is associated to a significant reduction of copper dissolved. XPS surface analysis of djurleite showed that lead nitrate favored the formation of Cu(OH)2 species. Lead was also detected on the surface (oxide or hydroxide). Sulphide and copper compounds (cyanide and sulphide) were reaction products responsible for inhibiting the dissolution of gold. Lead nitrate added in the Hunt leaching of bornite produced 99% gold extraction. Surface reaction products were similar to djurleite. The cyanide consumption (~4.4 kg/t NaCN) was not reduced by the addition of ammonia. Cyanidation of chalcopyrite showed a lower consumption of cyanide 0.33 kg/t NaCN compared to 0.21 kg/t NaCN for Hunt. No significant interferences were observed in gold leaching with a slurry containing chalcopyrite.
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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 | 0.000 | 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 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".