In this study, the surface optimization methodology was used to assess the effect of three independent variables—time, particle size and sulfuric acid concentration—on Mn extraction from marine nodules during leaching with H2SO4 in the presence of foundry slag. The effect of the MnO2/Fe ratio and particle size (MnO2) was also investigated. The maximum Mn extraction rate was obtained when a MnO2 to Fe molar ratio of 0.5, 1 M of H2SO4, −320 + 400 Tyler mesh (−47 + 38 μm) nodule particle size and a leaching time of 30 min were used.

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Based on the results obtained from a previous study investigating the dissolution of Mn from marine nodules with the use of sulfuric acid and foundry slag, a second series of experiments was carried out using tailings produced from slag flotation. The proposed approach takes advantage of the Fe present in magnetite contained in these tailings and is believed to be cost-efficient. The surface optimization methodology was used to evaluate the independent variables of time, particle size, and sulfuric acid concentration in the Mn solution. Other tests evaluated the effect of agitation speed and the MnO2/Fe2O3 ratio in an acid medium. The highest Mn extraction rate of 77% was obtained with an MnO2/Fe2O3 ratio of 1/2 concentration of 1 mol/L of H2SO4, particle size of −47 + 38 μm, and 40 min of leaching. It is concluded that higher rates of Mn extraction were obtained when tailings instead of slag were used, while future research needs to focus on determination of the optimum Fe2O3/MnO2 ratio to improve dissolution of Mn from marine nodules.

The importance of mine planning is often underestimated. Nonetheless, it is essential in achieving high performance by identifying the potential value of mineral resources and providing an optimal, practical, and realistic strategy for extraction, which considers the greatest quantity of options, materials, and scenarios. Conventional mine planning is based on a mostly deterministic approach, ignoring part of the uncertainty presented in the input data, such as the mineralogical composition of the feed. This work develops a methodology to optimize the mineral recovery of the heap leaching phase by addressing the mineralogical variation of the feed, by alternating the mode of operation depending on the type of ore in the feed. The operational changes considered in the analysis include the leaching of oxide ores by adding only sulfuric acid (H2SO4) as reagent and adding chloride in the case of sulfide ores (secondary sulfides). The incorporation of uncertainty allows the creation of models that maximize the productivity, while confronting the geological uncertainty, as the extraction program progresses. The model seeks to increase the expected recovery from leaching, considering a set of equiprobable geological scenarios. The modeling and simulation of this productive phase is developed through a discrete event simulation (DES) framework. The results of the simulation indicate the potential to address the dynamics of feed variation through the implementation of alternating modes of operation.

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