Recovery of zinc, gallium and indium from La Oroya zinc ferrite using Na<sub>2</sub>CO<sub>3</sub>roasting
Bibliographic record
Abstract
Process flowsheets for the recovery of zinc, indium and gallium from La Oroya zinc ferrite residue (19˙5%Zn, 26˙6%Fe, 0˙052%Ga, 0˙075%In) using Na2CO3 roasting are proposed. While several leaching flowsheets are discussed, the flowsheet where zinc ferrite is roasted with Na2CO3 and MnCO3, followed by two stages of leaching (hot water and H2SO4), iron reduction and precipitation of In and Ga as hydroxides, Fe as FeOOH and zinc as basic zinc sulphate from solution appears to be the most promising option for metals recovery from this material using Na2CO3 roasting. Sulphuric acid for leaching may be regenerated using either Na2SO4 metathesis or solvent extraction/ion exchange and Na2CO3 can be recovered for recycle to roasting from solution using precipitation and calcination of NaHCO3. Future research on these potential flowsheets is required, including possible methods for the recovery of iron, silver and gallium from the various process streams.
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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".