International Journal of Mining and Geo-Engineering
Year:2025 | Volume:59 | Issue:3|Papers Count:12

The global transition toward clean and sustainable energy systems has elevated lithium to a position of critical importance due to its exceptional electrochemical properties, low density, and lightweight characteristics. Lithium’s role in enabling the widespread adoption of electric vehicles (EVs) and portable electronics, coupled with the urgency of addressing climate change, underscores the need for efficient and sustainable resource exploration. This study focuses on assessing the potential for lithium extraction from brine sources in Kerman Province, Iran, with particular emphasis on the Shahrebabak region. Unlike previous studies that primarily focused on well-established lithium resources globally, this research explores an under investigated region in Iran, providing a new understanding of its lithium-bearing potential and associated challenges. By integrating advanced remote sensing techniques with field-based geochemical analyses, this study pioneers a comprehensive methodology that has not been applied to Iran's brine sources before. To identify lithium-rich zones, advanced remote sensing methods, including Landsat 8 and Sentinel-2 imagery, were employed alongside geochemical analysis conducted via Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Fifteen brine samples were collected at depths ranging from 0.5 to 2 meters, with lithium concentrations measured between 94 and 105 ppm. The Mg/Li ratios in these samples varied between 1.2 and 3.8, indicating potential challenges in achieving cost-effective extraction. Spectral Angle Mapper (SAM) analysis highlighted promising lithium-bearing zones, which were further validated through field sampling. The geochemical analysis of brine revealed that magnesium, potassium, sodium, and calcium are the dominant elements in the region, with lithium and boron present in trace amounts. Despite the presence of lithium, its relatively low concentration and high Mg/Li ratios suggest that the economic feasibility of large-scale lithium extraction in Shahrebabak remains limited. However, the study confirms the potential for lithium occurrence in Iran’s brine resources and highlights the need for further research into alternative extraction methods and the evaluation of other regions with more favorable geochemical conditions. This study contributes to the global discourse on clean energy and climate change mitigation by providing a foundational framework for lithium resource exploration in Iran. It aligns with the sustainable development goals by promoting environmentally compatible resource utilization, reducing greenhouse gas emissions, and fostering economic growth through the development of strategic clean energy resources. Further multidisciplinary research efforts are essential to fully realize Iran’s lithium potential and support the global transition to a greener energy future.

Considering the strategic relevance of nickel in a variety of industries, it is crucial to discover a method for extracting it from secondary sources. Spent reforming catalysts are hazardous to the environment, and require proper waste management techniques. In this research, the extraction of nickel from spent catalysts was studied and it was discovered that this process can dissolve a significant amount of nickel. Due to the high calcite content in the sample, its dissolution led to an elevation in pH, which negatively impacted bioleaching. It was observed that when the sample was added to the bioleaching solution after bacterial growth, the pH of the solution elevated less, and recovery improved. Moderately thermophilic bacteria had a better capability to reduce the pH and showed 66% nickel recovery which was slightly higher than the 61% recovery observed with mesophilic bacteria. Leaching tests and XRD analysis revealed that the portion of the nickel that is in the NiO phase is resistant to conventional leaching or bioleaching treatment, but reducing the sample with H2 as the pretreatment process can enhance the recovery of nickel. Reductive pretreatment of the sample can improve recovery, however it is not advised since it may have adverse environmental implications. The toxicity assessment test revealed that the bioleaching process with both cultures is able to reduce the risk of catalyst waste.

Mass movements are one of the natural tragedies that are more manageable than other natural disasters. Therefore, it is very important to understand this phenomenon in order to prevent the damage it can cause. Therefore, the present research was conducted in order to assess the risk of landslides and prepare a map of the severity of landslide risk in the Karganeh Watershed, Lorestan Province, Iran. Interpretation of aerial photos and field visit were used to prepare a landslide inventory map. In this research, 16 key landslide causal factors were identified to explore their spatial relationship with landslides. These factors reflect both inherent geomorphological characteristics and human influences related to landslide occurrences. Then, landslide hazard maps were built via tree models in geographic information system (GIS). Next, the information layer of the elements at risk and the degree of vulnerability of the elements were extracted. Finally, the landslide risk map was prepared by combining maps of the hazard map, elements at risk and degree of vulnerability of elements based on the general risk equation. The results presented that the (SVM) model provided greatly higher prediction accuracy of the landslide hazard map in the Karganeh Watershed via a/an (ROC) equal to 0.913. Additionally, the results of the risk map for the Karganeh Watershed indicated that 18.2% of the area is in the high-risk class. This area is equivalent to 5,349 hectares. Preparing a landslide risk map helps to focus the management work in the sectors that have a lot of risk and reduces the waste of time and money.

This study provides novel insights into the shear resistance behavior at the concrete-sand interface, focusing on the combined effects of sand grain size, concrete surface roughness, and soil relative density. While individual parameters have been explored in previous research, this work systematically examines their interactions to better understand interface shear strength. A series of large direct shear tests was conducted on concrete-sand samples with varying surface roughness values (Rmax = 0, 0.2, 4, and 8 mm) and granular materials with different mean particle sizes (D50 = 0.25 mm, 0.8 mm, and 2 mm). The granular materials were compacted to different relative densities (Dr = 30%, 60%, and 90%). The results revealed that increasing relative density from 30% to 60%, and from 30% to 90%, led to substantial rises in interface friction (approximately 105% and 306%, respectively). Coarser sand exhibited a more pronounced increase in interface friction angle than finer sand. Furthermore, increasing concrete surface roughness from 2 mm to 8 mm resulted in a 27% increase in the friction angle. These findings highlight the significant role of these parameters in governing the interaction between concrete and granular soil, offering valuable insights for applications in civil engineering.

The excavation and construction of underground stations are essential elements of modern urban infrastructure. This research article delves into the critical aspect of station construction within underground transportation systems, focusing specifically on stabilizing entrance walls of a metro station, particularly for Tunnel Boring Machine (TBM) entrances. The study conducts a comparative analysis between two support systems: the plastic concrete piles method and its combination with soil nailing, evaluating their efficacy in the context of TBM entrances. Employing both 2D and 3D Finite Element Modelling (FEM), the research investigates various soil constitutive models, including the Hardening Soil and Hardening Soil with Small Strain models. The findings emphasize the combined approach of utilizing plastic concrete piles with soil nailing as being more advantageous, demonstrating superior displacement control. Additionally, the comparison of modelling approaches indicates that the utilization of 3D modelling with the Hardening Soil with Small Strain model is recommended for numerical analysis of deep excavations near sensitive properties due to its ability to predict realistic ground movement distributions.

This study illustrates the use of 3D geoelectrical inversion modelling to accurately identify and characterize gold mineralization at a high potential zone in Iran. Nine parallel time domain geo-electrical profiles were acquired using a pole-dipole array, covering a total of 200 meters per profile with 10-meter electrode spacing. The induced polarization and resistivity data were processed and inverted using an unstructured tetrahedral mesh, enhancing the resolution and providing a more precise understanding of subsurface anomalies. The results revealed distinct chargeability and resistivity profiles, which were correlated with siliceous dikes and sulfide-rich zones, both of which are indicative of potential gold mineralization. Shallow anomalies (20-50 meters) align with hornfels layers and display characteristics typical of low-sulfidation epithermal systems, suggesting favorable conditions for gold mineralization. Furthermore, deeper anomalies (50-70 meters), associated with intrusive bodies, exhibit high resistivity and chargeability, consistent with gold-enriched siliceous veins. The study emphasizes the importance of integrating geophysical inversion techniques in gold exploration, as they provide a cost-effective and accurate method for identifying mineralized zones, reducing exploration uncertainties, and enhancing resource estimation. This approach contributes significantly to the efficiency and success of mining ventures by providing valuable insights into subsurface structures.

In most open pit mines, the first step in the operation cycle of a mining unit is drilling and blasting. One of the most important results of blasting in mines is rock fragmentation. The dimensions of the crushed parts, resulting from the blast, are effective in the costs of loading, haulage, and crushing operations. Many studies have been done in relation to understanding the blasting mechanism and introducing different charging patterns. One of the most practical charging methods that is used today in production blasts in mines is placing an air column along the charging column. This method leads to a change in blast mechanism compared to continuous charging by producing secondary pressures. In this research, the ratio of the optimal length of the air column in the limestone mass has been numerically studied in terms of rock damage. For the analysis and validation of the numerical model of the single blast hole, the field studies of other researchers have been used. In the present simulation, the length of the air column is designed between 0. 3 and 0. 9 meters. The results represent that by escalating the length of the air column up to 0. 7 meters, the pressure applied to the stemming column and fly rock velocity increase with the rate of 1. 18 and 1. 3, respectively. For longer lengths, this rate increases to 1. 58 and 2. 39, respectively. It is caused by excessive reduction of the stemming length. The radius analysis of damage in the limestone mass around the blast hole demonstrates that the maximum damage is achieved for the air column with a length of 0. 7 meters (air column length ratio was 21. 9).

In this study, two behavioral models—unified and multilaminate—are employed to simulate soil behavior. The unified model incorporates a non-associated flow rule along with the critical state concept. Additionally, the sub-loading surface concept is adopted to capture a smooth elastic-plastic transition. For numerical implementation, the implicit Euler method is used. The multilaminate model is based on a 13-plane framework, in which each plane exhibits elastic-plastic behavior. The overall soil response is obtained by integrating the elastic-plastic responses of the individual planes oriented in various directions at a material point. A set of unconventional constitutive equations is applied to each plane. This model captures soil softening behavior more realistically due to the use of a non-classical plasticity approach. Moreover, it accounts for the effect of induced anisotropy. To evaluate the models, four clay samples subjected to monotonic loading—under both drained and undrained conditions—were analyzed using both the unified and multilaminate models and were compared with experimental data. The results demonstrate that the unified model offers a more favorable representation of soil behavior.

Wastewater generated by the textile industry leads to significant color pollution and the release of hazardous substances. The adsorption process provides an effective method for mitigating organic pollutants, such as dye-laden wastewater. This study aimed to develop a Zeolite@Polydopamine composite that serves as a highly efficient material for the elimination of methylene blue dye from aqueous solutions. To attain maximum adsorption capacity, different effective parameters, such as temperature, contact time, dye concentration, adsorbent weight, and solution pH, were optimized. The optimal conditions for the removal process were established with a dye concentration of 10 mg/mL and an adsorbent weight of 30 mg. Under these conditions, the ideal contact time was achieved to be 30 min, with a pH level of 7 and a temperature maintained at 25°C. Evaluations of isotherm models and adsorption kinetics revealed that the adsorption process is best defined by the pseudo-second-order kinetic model in conjunction with the Freundlich isotherm. Additionally, the maximum adsorption capacity, as calculated by the Langmuir model, was found to be 70.92 mg/g. The negative values observed for both enthalpy and entropy suggest that this process of adsorption becomes more desirable at lower temperatures.

Accurate horizontal boundary definition is essential in geophysical exploration, as it helps delineate subsurface formations and understand tectonic activities. Traditional boundary determination methods often face challenges in resolution and accuracy, necessitating the development of improved techniques. Recently, a range of edge detection techniques has been developed based on derivatives of the field. This study compares the performance of several recently developed edge identification methods, including improvised logistics of the total horizontal gradient, improvised tilt angle of the horizontal gradient, enhanced version of the horizontal tilt angle, the total horizontal gradient of ImpTDX, Gompertz function, and improved edge detector. These methods are evaluated using synthetic models and Bouguer gravity data from the Tuan Giao area, Vietnam. The results showed that the regional structures tend mainly in the NW-SE direction, and some structures in the NE-SW direction.

TThis study has compared the performance of various optimizers in mineral resource classification using a multilayer perceptron artificial neural network (MLP) applied to a copper deposit in Peru. The optimizers Adam (Adaptive moment estimation), RMSprop (Root mean square propagation), SGD (Stochastic gradient descent), and Adagrad (Adaptive gradient algorithm) were evaluated to assess their impact on the spatial continuity of block classification. A total of 318,443 blocks were estimated using ordinary kriging, based on key variables including estimated grade, kriging variance, average sample distance, number of composited samples, the kriging Lagrangian, and geological confidence. The methodology involved a mixed multivariable block-by-block clustering using the k-prototypes algorithm, followed by block smoothing through an artificial neural network with different optimizers. Results show that the Adam optimizer achieved the highest overall accuracy (93%), outperforming both RMSprop and SGD (92%), as well as Adagrad (90%). In addition, Adam yielded a more homogeneous classification of mineral resources. It categorized 75,869 blocks as measured (1,395.99 Mt total tonnage, 5.40 Mt fine copper), 120,039 as indicated (2,208.72 Mt and 6.56 Mt fine copper), and 122,535 as inferred (2,254.64 Mt and 6.29 Mt fine copper). In conclusion, the model trained with the Adam optimizer demonstrated superior precision and stability in mineral resource classification, effectively mitigating the “spotty dog effect” and improving the geological coherence of the block model

The operational parameters of the roller screen substantially affect the efficiency and mechanical performance of its components, particularly those of the rolls. This study presents, for the first time, extensive coupled simulations employing the discrete element method-finite element method (DEM-FEM) to examine the effects of operating parameters on the mechanical behavior of rolls. This is achieved through the utilization of a realistic geometric model of the green pellets in conjunction with a hysteretic spring elastic-plastic contact model. The investigation revealed that decreasing the undersize gap from 9.75 mm to 9 mm led to increases of 20.27%, 29.71%, and 102.91% in the average force, total deformation, and equivalent stress exerted on the rolls, respectively. Furthermore, coupled DEM-FEM simulation tests of an industrial-scale roller screen were conducted for the first time, and the results obtained were compared with those from laboratory tests. The average force acting on the rolls of the laboratory roller screen was measured at 2.43 N. In contrast, simulations of a full-scale roller screen operating at capacities of 120 t/h and 200 t/h revealed average forces of 34.46 N and 54.06 N, respectively. The average total deformation observed in the rolls of the laboratory roller screen was measured at 4.27E-05 mm. In contrast, under industrial conditions, this deformation increased significantly to 1.89E-02 mm at a processing capacity of 120 t/h, and further escalated to 2.95E-02 mm at a capacity of 200 t/h