Effects of O<sub>2</sub> on aqueous SO<sub>2</sub> leaching of Co, Cu and Ni from discard smelter slag
Bibliographic record
Abstract
Abstract In the leaching of non‐ferrous smelter slag with a dissolved gas mixture of SO2 and O2, the behaviour of Co, Cu, Ni, Zn and Fe was studied in a 1‐L batch reactor. The parameters investigated include PSO2, PO2, temperature, particle size and pH. Co, Zn and Fe behaved similarly while Ni and Cu displayed distinguishable characters. The addition of O2 prevented the precipitation of Cu after dissolution, and increased acidity of the leaching solution. The increase in acid strength resulted in an increase in the extraction of Co, Zn and Fe. The effect of acidity on Cu and Ni extraction was however much weaker. The combination of SO2 and O2 was found to be a more effective oxidant of Fe(II) to Fe(III) than O2 alone. Simultaneous extraction of valuable metals and removal of Fe could be achieved by leaching at pH of 3 to 4. Maximum selectivities obtained for Co, Ni and Cu over Fe were 300, 2000 and 4000, respectively.
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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 | 0.000 | 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".