Experimental and modeling study demonstrates 72.6% copper recovery in pyrite-rich ore, indicating optimal leaching efficiency at controlled irrigation rates and acidity.
An integrated experimental modeling framework was developed to optimize the column hydrometallurgical leaching of a low–grade oxide–sulfide ore from the Miduk deposit, which contains high amounts of pyrite and iron and lead bearing phases. The primary objective was to maximize copper recovery while controlling the dissolution of impurities such as iron and lead. Bottle–roll tests were conducted on three particle sizes (75 µm, 9.51 mm, and 25.4 mm) at 25°C and 5–10% acid concentration. Reducing the particle size to 75 µm increased copper recovery to 81%, although it also resulted in higher acid consumption. A column leaching experiment was performed on a sample with d80 < 25.4 mm using a plexiglass column (125 cm height, 15 cm diameter) at a flow rate of 3 mL/min, yielding cumulative recoveries of 72.6% Cu, 20.51% Fe, and 13.87% Pb. During leaching, porosity decreased by approximately 6% and permeability declined by a factor of 1.5, attributed to secondary mineral precipitation and bed compaction. Flow and mass transfer simulations were conducted using Darcy based, Richards, and mass transfer models, with the Richards model providing the best agreement with the experimental results. In the numerical modeling stage, the systematic effects of key variables, including acid concentration, irrigation rate, and initial bed porosity, were evaluated. The initial porosity was derived from the crushing induced particle size distribution and incorporated into the sensitivity analysis. The results indicated that optimal operating conditions include an irrigation rate of 2–3 mL/min, an initial porosity of 20–30%, and an acid concentration of approximately 5%. This integrated approach enables a quantitative assessment of the coupled hydraulic and chemical behavior of the ore bed, operating conditions, and the co–dissolution of target and impurity elements. It provides a reliable tool for predicting and optimizing the leaching performance of low–grade and complex copper ore.
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Farhadi et al. (2026) studied this question.
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