Atmospheric leaching of nickel and cobalt from nickel saprolite ores using the Starved Acid Leaching Technology
Bibliographic record
Abstract
There is great potential to recover nickel from below cut-off grade nickel saprolite ores using the Starved Acid Leach Technology (SALT). Nickel saprolite ores are normally mined as feed to Fe-Ni smelters or Ni matte smelting operations. The smelting processes typically require high Ni cut-off grades of 1.5 to 2.2% Ni, depending on the operation. These very high cutoff grades result in a significant portion of the saprolite profile being regarded as “waste” and hence having little to no value. The below cut-off grade (waste) material can be processed by atmospheric acid leaching with “starvation” levels of acid addition. The leached nickel and cobalt may be recovered as a mixed hydroxide (or alternate product). The mixed hydroxide may be added to the saprolite smelting operation feed system to increase the nickel production of the smelter or may be refined separately. The technical development of the SALT process will be described along with an economic summary. The SALT process has great potential to treat many Indonesian Nickel ores that are too low a grade for current technology.
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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".