Multilevel factorial optimisation of Acid-to-Ore ratio and solids concentration in hydrometallurgical recovery of nickel from laterite ore
Year: 2025
Type: article
Abstract: This study applies a multilevel factorial design to optimise nickel (Ni) extraction in a High-Pressure Acid Leaching (HPAL) autoclave, examining the influence of slurry solid content and acid-to-ore (A/O) ratio on Ni yield, selectivity (Ni/(Al+Fe)), and scale formation. A regression model was established to predict these responses across varying A/O ratios and solid contents. Using Minitab® statistical software, response surface methodology (RSM) was employed to identify process conditions that balance maximised Ni yield, enhanced selectivity and reduced scale formation. To predict outputs beyond the experimental range, the complex models generated in Minitab® were simplified into ‘linear + quadratic + interaction terms’ using the least squares method in Matlab®. Results indicate that higher Ni yield (> 95 wt.%) is achieved at a lower slurry solid content (< 27 wt.%) and higher A/O ratios (> 0.35), whereas higher solution purity (selectivity > 3) is favoured at lower A/O ratios with preferably lower solid content (∼22 wt.%). Scale formation increases significantly with higher solid content and A/O ratios exceeding 0.35. Optimisation revealed that a compromise between Ni yield, selectivity, and scale minimisation is necessary, with the highest composite desirability (0.68) obtained at 22 wt.% solid content and an A/O ratio of 0.35. The findings provide valuable insights for industrial leaching process optimisation, highlighting the trade-offs between maximising Ni recovery, limiting impurity dissolution and minimising scale formation.
Source: Results in Engineering
Institutions: Centre National de la Recherche Scientifique, IMT Mines Albi, Centre de Recherche d'Albi en génie des Procédés, des SOlides Divisés, de l'Énergie et de l'Environnement, Université Paris Sciences et Lettres, Centre Energie Environnement Procédés, École Nationale Supérieure des Mines de Paris
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,940
Award: G7156135686
OpenAlex ID: W4413290041
