Nickel Extraction from Olivine: Effect of Carbonation Pre-Treatment
Bibliographic record
Abstract
In this work, we explore a novel mineral processing approach using carbon dioxide to promote mineral alterations that lead to improved extractability of nickel from olivine ((Mg,Fe)2SiO4). The precept is that by altering the morphology and the mineralogy of the ore via mineral carbonation, the comminution requirements and the acid consumption during hydrometallurgical processing can be reduced. Furthermore, carbonation pre-treatment can lead to mineral liberation and concentration of metals in physically separable phases. In a first processing step, olivine is fully carbonated at high CO2 partial pressures (35 bar) and optimal temperature (200 °C) with the addition of pH buffering agents. This leads to a powdery product containing high carbonate content. The main products of the carbonation reaction include quasi-amorphous colloidal silica, chromium-rich metallic particles, and ferro-magnesite ((Mg1−x,Fex)CO3). Carbonated olivine was subsequently leached using an array of inorganic and organic acids to test their leaching efficiency. Compared to leaching from untreated olivine, the percentage of nickel extracted from carbonated olivine by acid leaching was significantly increased. It is anticipated that the mineral carbonation pre-treatment approach may also be applicable to other ultrabasic and lateritic ores.
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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".