Effect of Magnesium on Pressure Leaching of Moa Laterite Ore
Bibliographic record
Abstract
The magnesium content of laterite ore has a significant impact on the quantity of sulphuric acid required to achieve the target nickel extraction by the high pressure acid leach (HPAL) process, both through direct consumption of acid when magnesium-bearing minerals are dissolved and through "buffering" effects via bisulphate ion equilibria at temperature in the leach reactor. This paper presents the results of HPAL batch tests conducted by Sherritt Technologies in Fort Saskatchewan, Alberta, Canada with ore samples from the Moa Nickel Pedro Sotto Alba plant at Moa, Holguin, Cuba along with a comparison of the laboratory results with operating data from Moa. A significant variation in acid requirement has been demonstrated over a relatively narrow range of feed magnesium content. Further, the quantitative results of the laboratory tests allow a model to be formulated for the most economic consumption of acid at Moa. Résumé La teneur en magnésium du minerai de latérite a un impact important sur la quantité d'acide sulfurique requise pour atteindre l'objectif d'extraction de nickel par le procédé de lessivage acide à haute pression (HPAL), tant par consommation directe d'acide lorsque les minéraux porteurs de magnésium sont dissous, que par des effets "tampons" par l'intermédiaire d'équilibres de l'ion bisulfate à la température du réacteur de lessivage. Cet article présente les résultats d'essais en lot de HPAL effectués par Sherritt Technologies à Fort Saskatchewan, Alberta, Canada, avec des échantillons de minerai de l'usine de Moa Nickel Pedro Sotto Alba, à Moa, Holguin, Cuba, ainsi qu'une comparaison des résultats de laboratoire avec des données d'opérations de Moa. On montre une variation importante du besoin en acide sur une gamme relativement étroite de la teneur en magnésium de l'alimentation. De plus, les résultats quantitatifs des essais de laboratoire ont permis de développer un modèle de consommation d'acide la plus économique à Moa.
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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 | 0.001 |
| 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 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".