Complex gangues and low-quality waters are a concern for the mining industries, particularly in water shortage areas, where the closure of hydric circuits and reduction in water use are essential to maintain the economic and environmental sustainability of mineral processing. This study analyzes the phenomena involved in the water recovery stage, such as sedimentation of clay-based tailings flocculated with anionic polyelectrolyte in industrial water and seawater. Flocculation–sedimentation batch tests were performed to ascertain the aggregate size distribution, the hindered settling rate, and the structure of flocs expressed through their fractal dimension and density. The aggregates’ properties were characterized by the Focused Beam Reflectance Measurement (FBRM) and Particle Vision Microscope (PVM) techniques. The impact of the type of water depends on the type of clay that constitutes the suspension. For quartz/kaolin, the highest performance was obtained in industrial water, with bigger aggregates and faster settling rates. However, the tailings composed of quartz/Na-montmorillonite reversed this trend. The type of water impacted the efficiency of primary-particle aggregation. The trials in industrial water generated a portion of non-flocculated particles, which was observed through a bimodal distribution in the unweighted chord-length distribution. This behavior was not observed in seawater, where a perceptible fraction of non-flocculated particles was not found. The additional cationic bonds that offer seawater favor finer primary-particle agglomeration for all tailings types.
In this work, a recycling route for spent Li-ion batteries (LIBs) was developed. For this, the recovery of the metal content in both electrodes (anode and cathode) was investigated. Based on these results, an economic analysis of this recycling process was carried out. The obtained results showed that more than 90% of the material contained in both electrodes was recycled. The dissolution with acetic acid of the metals present in the active cathodic material is thermodynamically viable and the addition of a reducing agent such as hydrogen peroxide improved the spontaneity of the reaction. Dissolutions close to 100% for Li and Co were obtained. In addition, it was determined that the synthesis of lithium and cobalt valuable compounds was viable from the leach liquor, recovering approximately 90% of Co as cobalt oxalate, and 92% of Li as lithium carbonate. Furthermore, carbon graphite and Cu were fully recovered (100%) from the anodes. Finally, the results of the economic analysis showed that the recovered products have a high commercial value and industrial interest, providing an environmentally and economically viable process.
Polymetallic nodules, also called manganese nodules (due to their high content of this element), contain various valuable metals such as Cu, Ni and Co. These seabed minerals are a good alternative source of Co and Mn due to the decrease in the grade of mineral deposits on the earth’s surface. For the treatment of manganese nodules, acid-reducing leaching is apparently the most attractive, due to its low cost compared to other processes, short operational times, and it is more friendly to the environment. In this investigation, the extraction of Mn and Co from manganese nodules from two different locations was studied in acid media and by reusing a steel slag obtained from a steel smelting process. An ANOVA analysis was performed to determine the most appropriate Manganese Nodule/Fe(res) ratio and time to dissolve Co and Mn from the nodules. Effect of temperature on the process was evaluated, and then a residue analysis was carried out. Finally, it was discovered that the best results were obtained when working at 60 °C in a time of 15 min, obtaining extractions of approximately 98% Mn and 55% Co. Additionally, the formation of polluting elements was not observed, nor the precipitation of Mn and Co species in the studied residues.
Artificial intelligence and machine learning algorithms have an increasingly pervasive presence in all fields of science due to their ability to find patterns, model dynamic systems, and make predictions of complex processes. This review aims at providing the researchers in the mineral processing area with structured knowledge about the applications of machine learning algorithms to the leaching process, showing the applications of techniques such as artificial neural networks (ANN), support vector machines (SVM), or Bayesian networks (BN), among others. Additionally, future perspectives are indicated, emphasizing both the generalization of the algorithms and the productive potential of the application of modeling, simulation, and optimization of the tools studied to industrial processes.
In areas where access to water for mineral processing is limited, the direct use of seawater in processing has been considered as an alternative to the expense of its desalination. However, efficient flotation of copper sulfides from non-valuable phases is best achieved at a pH > 10.5, and raising the pH of seawater leads to magnesium precipitates that adversely affect subsequent tailings dewatering. Seawater pre-treatment with lime can precipitate the majority of magnesium present, with these solids then being removed by filtration. To understand how such treatment may aid tailings dewatering, treated seawater (TSw) was mixed with raw seawater (Rsw) at different ratios, analyzing the impact on the flocculated settling rate, aggregate size as measured by focused beam reflectance measurement (FBRM), and vane yield stress for two synthetic clay-based tailings. A higher proportion of Tsw (10 mg/L Mg2+) led to larger aggregates and higher settling rates at a fixed dosage, with FBRM suggesting that higher calcium concentrations in Tsw may also favor fines coagulation. The yield stress of concentrated suspensions formed after flocculation decreased with higher proportions of Tsw, a consequence of lower flocculant demand and the reduced presence of precipitates; while the latter is a minor phase by mass, their high impact on rheology reflects a small particle size. Reducing magnesium concentrations in seawater in advance of use in processing offers advantages in the water return from thickening and subsequent underflow transport. However, this may not require complete removal, with blending Tsw and Rsw an option to obtain acceptable industrial performance.
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