Optimizing Zinc Recovery in Sulfide Mineral Flotation for Geometallurgical Characterization

Mineral recovery in the mining industry is a global challenge [1, 2], especially in the extraction of metals such as zinc, which is crucial for various industrial applications from galvanization to alloy manufacturing. According to the United States Geological Survey, global zinc production in 2021 was approximately 13 million tons, with China, Peru and Australia being the main producers [3, 4]. The growing demand for zinc, driven by its use in corrosion protection and the automotive industry, has intensified the need to optimize recovery processes to ensure a continuous and efficient supply [5-7]. This demand is expected to continue to increase due to the growth of the electric vehicle industry, where zinc is an essential component in batteries and other electronic devices [7].

Zinc recovery methods have evolved significantly in recent decades, but still face significant technical challenges [8-10]. Traditional flotation methods have been complemented by advanced biohydrometallurgy and leaching techniques; however, the efficiency of these methods can be affected by variability in the mineralogy of the deposits and the specific conditions of each mine [11, 12]. Although zinc recovery by flotation has been widely studied, previous research has not comprehensively addressed the complex interactions between different minerals present in geometallurgically complex deposits such as those in the Oyón Province. Studies such as those by Jia et al. [7] have highlighted the influence of sulfide species in inhibiting selective zinc flotation, but have not offered solutions that address mineralogical variability. This study builds on this background and seeks to close these gaps by implementing advanced mineralogical characterization techniques and a robust experimental design that optimizes zinc recovery under specific local conditions.

For example, a study conducted by Chandra and Gerson [13] highlighted how zinc activation in the presence of pyrite and other sulfide minerals can inhibit selective zinc flotation due to complex galvanic interactions that are not always predictable and require precise control of the chemical environment.

Peru is the second largest producer of zinc in the world, with an annual production exceeding 1.4 million tons, contributing significantly to the country's economy [14-16]. Zinc mining in Peru is a vital industry, with regions such as Ancash, Pasco and Lima playing crucial roles in the extraction of this metal [17]. However, the industry faces significant challenges related to the efficiency of recovery processes and environmental sustainability. The sulfide mineral deposits in these regions present a geological complexity that makes effective zinc recovery difficult, underlining the need for advanced research to improve processing techniques [17]. In particular, the presence of gangue minerals such as pyrite, which compete with sphalerite (main zinc mineral) for flotation reagents, represents a significant challenge for concentrator plants.

In the province of Oyón, located in the Lima region, the extraction of sulfide minerals is a key economic activity. The deposits in Oyón contain valuable species such as sphalerite, marmatite, galena, and traces of gold and electrum. However, zinc recovery in these deposits faces obstacles due to mineralogical complexity and the presence of gangue species that interfere with the flotation process. Previous studies have shown that variability in mineralogical composition and suboptimal operating conditions can lead to suboptimal zinc recovery, negatively affecting the profitability and sustainability of mining operations [18]. Furthermore, the mountainous geography and extreme climatic conditions of the region can influence the effectiveness of processing techniques, making it essential to develop strategies adapted to these local conditions.

Despite advances in flotation techniques and mineralogical characterization, significant knowledge gaps remain that limit the efficiency of zinc recovery. One of the main challenges is the selective activation of sphalerite in the presence of pyrite and other sulfide minerals. Galvanic interaction between these minerals can inhibit selective zinc flotation, a problem that has been documented but not fully resolved [13]. Variability in mineralogical composition, particularly the presence of marmatite, a high-iron variant of sphalerite, can further complicate the flotation process due to their different surface properties and chemical reactivity.

Furthermore, accurate dosing of reagents such as ZnSO₄ and NaCN remains an area with room for improvement, as incorrect dosing can result in significant zinc losses and increased operating costs [19]. Optimization of these reagents is critical to maximizing zinc recovery and minimizing economic losses. Other studies have shown that flotation pulp pH is a critical factor affecting zinc recovery. However, the interaction of multiple operational variables and their combined impact on process efficiency has not been fully explored. This study addresses these knowledge gaps through a comprehensive approach that combines advanced mineralogical characterization techniques and rigorous experimental design to optimize flotation conditions [8].

Regarding this topic, there is little research that has comprehensively addressed the optimization of zinc recovery in sulfide minerals, which makes it a particularly relevant and interesting field of study. Although there are some previous studies that have explored various methodologies and techniques to improve zinc recovery, there are still important gaps in knowledge and areas with considerable potential for improvement.

According to the study by Wu et al. [20] aimed to optimize zinc recovery in the flotation of sulfide minerals by removing surface oxidation products, which reduce mineral hydrophobicity and hinder selective collector adsorption. To achieve this, mechanical (sonication and quartz attrition) and chemical (pH adjustment and use of complexing agents) methods were applied on various sulfide minerals. The effectiveness of these treatments was evaluated by correlating the amount of oxidation products removed with flotation results. "Cleaning" methods proved to be effective and selective, improving mineral hydrophobicity and collector adsorption, resulting in increased flotation efficiency. However, this study does not address zinc recovery optimization under complex geometallurgical conditions such as those at Oyón, Peru. This investigation will integrate advanced mineralogical characterization with a robust experimental design to optimize flotation conditions and maximize zinc recovery, addressing the mineralogical variability and specific conditions of the Oyón deposits.

On the other hand, there is the research carried out by Clarke et al. [21], the objective of this research was to optimize zinc recovery from sulfide ores by removing toxic heavy metals using potassium permanganate (KMnO₄). Using Aspen Plus software and the Taguchi method, a new configuration was evaluated where KMnO₄ is produced from cobalt purification sludge with MnO₂, and H₂SO₄ is obtained from sulfur compounds released during ore leaching. The Taguchi experimental design determined optimal conditions, which were used for simulation and sensitivity analysis of the process. These conditions included a H₂SO₄ concentration of 70 g/L, temperature of 90℃, stirring speed of 200 rpm, reaction time of 1.5 hours, particle size of 500 μm, solid-liquid ratio of 1:2, 40% additive by weight and oxygen pressure of 1.5 MPa. The results showed that the conversion of sulfide gases to H₂SO₄, KMnO₄ recovery, and toxic heavy metal removal reached 98%, 91%, and 99% respectively. However, their research does not address specific optimization for zinc recovery under the complex geometallurgical conditions of Oyón, Peru, which will be the focus of this research.

Likewise, there is a study carried out by Dominy et al. [22], where the objective of this investigation was to optimize zinc recovery in sulfide minerals by applying advanced oxidation processes (AOP) based on metal sulfides, known for their catalytic performance and stability. Aspen Plus software and the Taguchi method were used to evaluate a new configuration that uses potassium permanganate (KMnO₄) obtained from cobalt purification sludge and sulfuric acid (H₂SO₄) generated from sulfur gases released in leaching. Optimal operating conditions were established using the Taguchi experimental design and simulations and sensitivity analyses were performed. The results showed that under optimized conditions (70 g/L H₂SO₄, 90℃, 200 rpm, 1.5 hours, 500 μm particle size, 1:2 solid-liquid ratio, 40% additive by weight, and 1.5 MPa oxygen pressure), the conversion of sulfide gases to H₂SO₄, KMnO₄ recovery, and toxic heavy metal removal were 98%, 91%, and 99% respectively. However, this research does not address the specific integration of metal sulfide-based AOPs for zinc recovery in complex geometallurgical contexts, which will be the main focus of my research, seeking to improve the efficiency and sustainability of zinc recovery in Oyón, Peru.

The main objective of this study is to optimize zinc recovery from sulfide mineral deposits in the province of Oyón by implementing an experimental design that evaluates reagent dosage and pH of the flotation pulp. Using advanced optical and electron microscopy techniques, a detailed characterization of the mineral species present will be performed, allowing for the design of more efficient and sustainable processing strategies. This approach not only considers the individual properties of the minerals, but also their complex interactions and how this affect flotation efficiency.

Compared to previous research, this study not only focuses on the optimization of individual variables, but also considers the complex interactions between different operational factors. In addition, advanced statistical analysis techniques will be implemented to identify optimal flotation conditions, thereby improving zinc recovery and concentrate quality. This comprehensive approach not only optimizes the metallurgical process, but also contributes to the socio-economic development of the mining communities involved, promoting sustainable and efficient practices.

The relevance of this study lies in its potential to significantly improve the efficiency and sustainability of zinc recovery in the province of Oyón. By addressing existing knowledge gaps and applying a comprehensive optimization approach, this research will not only benefit the local mining industry, but will also offer a replicable model for other regions with similar deposits. The results of this study will contribute to the development of more efficient and sustainable mining practices, supporting the Peruvian economy and protecting the environment.

This study differs from previous work by integrating a detailed analysis of the geometallurgical characterization with a robust experimental design that considers the interactions between multiple operational variables. Research such as that of Chen et al. [18], they have highlighted the importance of mineralogical characterization, but have not fully addressed how these characteristics can be integrated into a flotation optimization model. This study also considers long-term sustainability, assessing not only zinc recovery but also the environmental impact and economic viability of the proposed practices.

Unlike previous research, which has explored zinc sulfide mineral flotation more generally, this study is distinguished by its comprehensive focus on optimization under complex geometallurgical conditions, particularly in deposits in the Oyón Province. The integration of advanced optical microscopy and TIMA electron microscopy, combined with a multifactorial experimental design, represents a novel contribution to the field. Furthermore, the use of predictive modeling and statistical optimization allows for greater precision in the control of operational variables, significantly improving the efficiency and sustainability of zinc recovery.

3.1 Optical microscopy of the head mineral

Modal analysis of a representative sample of head ore was carried out at a granulometry of 75% - 200 mesh, using a polarizing light optical microscope, identifying copper species such as chalcopyrite with a distribution of 5.37%, and 97.27% release, Zn species such as sphalerite with a volume of 17.24%, and 99.51% free species, Pb species such as galena with a distribution of 7.41% and 97.73% free species, in addition traces of gold and electrum were observed, species considered to be of economic value, and are represented in Table 1.

Table 1. Species identified with optical microscopy

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Figure 1. Volumetric distribution of mineralogical species

Table 1 and Figure 1 show the volumetric distribution of the mineral species, which showed that gangues were found occupying a volume of 51.95%, a value that corresponds to just over half of the volume of the sample. In addition, iron sulfides such as pyrite and pyrrhotite could be observed with distributions of 15.32% and 1.24%, respectively. 

The results from optical microscopy and TIMA electron microscopy show a strong consistency in identifying the main mineral species present in the ore, particularly with regards to sphalerite, chalcopyrite, and pyrite. Optical microscopy revealed a sphalerite distribution of 17.24% with 99.51% free species, which was closely matched by the TIMA analysis, where sphalerite/marmatite was recorded at 15.21% with 99.69% free species. Similarly, chalcopyrite was detected in both methods with a distribution of 5.37% (optical microscopy) and 4.98% (TIMA), reinforcing the reliability of these findings. However, the TIMA analysis provided additional insights into gangue mineral composition, identifying quartz (9.56%), muscovite (0.18%), and epidote (0.28%), which were either not detected or less clearly differentiated by optical microscopy. This complementary relationship between both techniques enhances the overall understanding of the mineralogical composition, confirming that TIMA microscopy can offer a more detailed characterization of gangue minerals and their textural relationships, while optical microscopy provides essential information on the liberation and interlocking of economic minerals.

3.2 Interlocking of minerals

In the modal analysis, 5365 free particles and 98 entangled particles were counted, 18 entangled particles of gn-ef-py were observed, occupying a volume of 0.38%, and different types of entanglement, as shown in Table 1 and in the pie chart in Figure 1. Also, the main micrographs are represented in Figure 2 and Figure 3 as well as in Table 2.

Table 2. Distribution and release of entanglements

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Figure 2. Total distribution of interlaced species

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Figure 3. Micrograph with presence of cp, gn, hm, gt and GGs (left), micrograph with presence of py, gn, ef and GGs (middle), micrograph with presence of cp, ef and GGs (right)

Table 3. Species identified with TIMA electron microscopy

3.3 Interlocking of minerals

A representative sample of polymetallic mineral was observed under the Tima electron microscope, in order to identify and classify the species of economic value and waste, by size, composition, and texture. Table 3 represents the total number of species identified by the electron microscope.

3.3.1 Zinc mineral species and their mineralogical ties

Table 4. Species identified with electron microscopy – Zn

The largest contribution of Zn corresponded to marmatitic sphalerites with a distribution value of 99.69% of the total Zn species. In addition, oxidized Zn species such as Smithsonite could be identified, with a distribution of 0.31%, as observed in Table 4.

1. Degrees of liberation of marmatitic sphalerites

A liberation degree of 70.09% was determined for the marmatitic sphalerites, in addition, 25.77% was observed forming bonds and 4.41% was identified as occluded in another mineral species. Table 5 describes the analysis of the liberation degrees by size, and Figure 4 represents comparative bar graphs of the liberation degrees by size.

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Figure 4. Representation of the percentage of liberation – sphalerite/marmatite

Table 5. Volumetric distribution according to its granulometry

2. Mineralogical assemblages of sphalerite

Sphalerite was observed forming groupings with pyrite, calcite and quartz, with distribution values of 5.32%, 9.60% and 4.28%, respectively. Other complex assemblages representing 2.05% of the sample volume were also identified, as shown in Table 6 and Figure 5.

Table 6. Zn mineral associations

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Figure 5. Particles according to their release - Zn

3.4 Chemical analysis of the head ore

A representative sample of the sulfide ore batch was assayed using volumetric methods to determine the grades of Pb, Zn and Cu, while for Au and Ag, the dry method was used. The results of the chemical analysis are described in Table 7.

Table 7. Zn mineral associations

3.5 Standard flotation process

3.5.1 Standard bulk flotation of Pb-Cu

The beneficiation of polymetallic sulfide minerals in the province of Oyón is carried out through the flotation process in stockpile plants, which is carried out in a first stage of bulk flotation of Pb-Cu, depressing the Zn sulfides. The standard conditions of the first stage of bulk flotation of Pb-Cu are detailed in Table 8, and the metallurgical balance in Table 9 represents the results of the replication of the process at laboratory level, demonstrating a displacement of 13.53% of Zn, with a grade of 6.54% in the Pb-Cu bulk concentrate.

Table 8. Operating conditions of Pb-Cu flotation

Table 9. Metallurgical balance of standard Pb-Cu flotation

3.5.2 Standard Zn flotation

The tailings from the bulk Pb-Cu flotation were fed to the standard Zn flotation circuit, for which they were conditioned with CuSO₄ (5%) activating reagent at a pH of 11. The operating conditions for the standard Zn flotation are described in Table 10, and the results of the laboratory tests demonstrated a recovery of 96.35% of Zn with a quality of 42.74%, as represented in the metallurgical balance in Table 11.

3.6 Evaluation of zinc displacement in bulk Pb-Cu flotation

Based on the mineralogy, bulk Pb-Cu flotation tests were developed in order to evaluate the influence of the depressing reagents ZnSO₄ (5%) and NaCN (1%), in addition to the pH of the pulp, keeping the other operating variables constant (see Table 12), to minimize the displacement of Zn sulfides in the bulk Pb-Cu concentrate. Table 12 shows an experimental arrangement of 3 factors, two levels, and two replicas, whose best test corresponds to the one of order N°7, reaching a recovery of 95.71% of Pb, 94.34% of Cu, and 79.29% of Ag. Likewise, a minimum displacement of zinc was achieved in the bulk concentrate, with a recovery value of 5.14% of Zn in the bulk, and a quality of 1.24%, for which 120 g/TM of ZnSO₄, 60 g/TM of NaCN were dosed, at a pH of 9.

The minimum and maximum values of the variables are described in Table 13. In addition, the factorial experimental design of metallurgical tests.

Table 10. Operating conditions of Zn flotation

3.6.1 Analysis of variance for zinc displacement in bulk Pb-Cu flotation

The ANOVA for the displacement of Zn in the bulk concentrate showed that the flotation pH was a determining factor in controlling the displacement, with a contribution value of 72.59%, as well as ZnSO₄ and double and triple interactions being determining factors in controlling the displacement of zinc in the Pb-Cu bulk. The ANOVA results are shown in Figure 6, which represents the normal graph of standardized effects, and the level of significance of the variables studied, in controlling the displacement of Zn in the Pb-Cu concentrate.

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Figure 6. Standardized effects graph – Zn recovery in Pb-Cu bulk flotation

Table 11. Metallurgical balance of standard Zn flotation

Table 12. 3-factor, 2-level, 2-replicate factorial design for bulk Pb-Cu flotation

3.6.2 Experimental designs for zinc flotation

To evaluate the Zn flotation, the parameters of the bulk Pb-Cu flotation test No. 7 were taken into account, in order to prepare a representative sample to evaluate the recovery and quality of Zn, for which, the reagent dosage variables CuSO₄ (5%) and Z-11 (1%) were evaluated under the minimum and maximum parameters, 150 to 300 for CuSO₄ (5%) and 40 to 80 for Z-11 (1%). Table 13 details the 2-level, 2-factor, and 2-replica factorial experimental design template, and their respective response variables, showing that the best results achieved a recovery of 97.61% of Zn with a quality of 48.06%, dosing 300 g/TM of CuSO₄ (5%), and 40 g/TM of Z-11 (1%).

Table 13. 2-factor, 2-level, 2-replicate factorial design for Zn flotation

1. Analysis of variance for zinc recovery

The analysis of variance for Zn recovery showed that the CuSO₄ dosage variable (5%) contributed 51.72%, and the interaction of the reagents used contributed 45.18% to the recovery variable. As a result of the analysis of the Zn recovery data, the model that predicts this response variable is presented, which presented a predictive correlation coefficient of 99.66%.

Rec. Zn(%) = 54.082 + 0.15894(CuSO₄) + 0.4771(Z-11) - 0.001953(CuSO₄*Z-11)

The charts in Figure 7 and Figure 8 graphically represent the standardized effects of the variables studied, with a reliability of 95%, which shows that the variables studied and their interactions are determining factors in determining the response variable.

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Figure 7. Pareto chart of Zn recovery in Zn flotation

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Figure 8. Main effects plot of Zn recovery in Zn flotation

2. Analysis of variance for zinc grade in concentrate

The ANOVA for the quality in the concentrate showed that the greatest contribution is made by the dosage of the reagent CuSO₄, with a value of 43.55%, as well as the interaction of the variables with a value of 35.12%. As a result of the analysis of variance, a mathematical model was presented, which predicts the quality of zinc in the flotation process, with a predictive correlation coefficient value of 54.54%. The regression equation:

Ley Zn(%) = 16.94 + 0.1256(CuSO₄) + 0.282(Z-11) - 0.001527(CuSO₄*Z-11)

The charts in Figure 9 and Figure 10 graphically represent the standardized effects of the variables studied, with a reliability of 95%, which demonstrates the greater contribution made by the dosage of copper sulphate, and the interaction of the variables studied, on the response variable.

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Figure 9. Pareto chart of Zn law in Zn flotation

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Figure 10. Contour plot of Zn law in Zn flotation

3. Zn recovery optimization

Using the statistical software Minitab 19, the independent variables were optimized to maximize the quality of Zn in the concentrate, as detailed in Table 14. The values of the optimized variables are presented in Figure 11.

Table 14. Adjustment of independent variables to maximize Zn recovery and grade

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Figure 11. Optimization of Zn flotation