The leaching of minerals is one of the main unit operations in the metal dissolution process, and in turn it is a process that generates fewer environmental liabilities compared to pyrometallurgical processes. As an alternative to conventional leaching methods, the use of microorganisms in mineral treatment processes has become widespread in recent decades, due to advantages such as the non-production of emissions or pollution, energy savings, low process costs, products compatible with the environment, and increases in the benefit of low-grade mining deposits. The purpose of this work is to introduce the theoretical foundations associated with modeling the process of bioleaching, mainly the modeling of mineral recovery rates. The different models are collected from models based on conventional leaching dynamics modeling, based on the shrinking core model, where the oxidation process is controlled by diffusion, chemically, or by film diffusion until bioleaching models based on statistical analysis are presented, such as the surface response methodology or the application of machine learning algorithms. Although bioleaching modeling (independent of modeling techniques) of industrial (or large-scale mined) minerals is a fairly developed area, bioleaching modeling applied to rare earth elements is a field with great growth potential in the coming years, as in general bioleaching has the potential to be a more sustainable and environmentally friendly mining method than traditional mining methods.

Polymers have interesting physicochemical characteristics such as charge density, functionalities, and molecular weight. Such attributes are of great importance for use in industrial purposes. Understanding how these characteristics are affected is still complex, but with the help of molecular dynamics (MD) and quantum calculations (QM), it is possible to understand the behavior of polymers at the molecular level with great consistency. This study was applied to polymers derived from polyacrylamide (PAM) due to its great use in various industries. The polymers studied include hydrolyzed polyacrylamide (HPAM), poly (2-acrylamido-2-methylpropanesulfonate) (PAMPS), polyacrylic acid (PAA), polyethylene oxide polymer (PEO), and guar gum polysaccharide (GUAR). Each one has different attributes, which help in understanding the effects on the polymer and the medium in which it is applied along a broad spectrum. The results include the conformation, diffusion, ion condensation, the structure of the water around the polymer, and interatomic polymer interactions. Such characteristics are important to selecting a polymer depending on the environment in which it is found and its purpose. The effect caused by salinity is particular to each polymer, where polymers with an explicit charge or polyelectrolytes are more susceptible to changes due to salinity, increasing their coiling and reducing their mobility in solution. This naturally reduces its ability to form polymeric bridges due to having a polymer with a smaller gyration radius. In contrast, neutral polymers are less affected in their structure, making them favorable in media with high ionic charges.

The Mine-to-Mill (M2M) approach aims to enhance efficiency and reduce costs in the mineral processing industry by optimizing the mining and processing stages. M2M integrates orebody characterization, blasting, and downstream processes, such as grinding and flotation, demonstrating that material fragmentation directly impacts downstream efficiency. This review studies the development and applications of fragmentation models in M2M integration and optimization, finding that their study is divided into three phases. In the first, the potential of M2M is investigated through simulation models that improve fragmentation in blasting to optimize grinding. The second focuses on the practical application of these models in mines, while the third phase integrates geometallurgical data into mine block models, enhancing production planning and selective ore extraction. The M2M integration has demonstrated significant improvements in plant performance, particularly in increasing grinding efficiency through optimized blast fragmentation. The literature also emphasizes the role of optimizing crushing and grinding conditions through models and circuit adjustments to enhance performance and reducing energy consumption. Geometallurgy plays a crucial role in plant optimization by identifying areas with better processing characteristics and adjusting operating parameters to maximize efficiency. Recent studies have shown how the implementation of integrated models can increase the profitability and sustainability of mining operations.

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.

In the mining industry, key unit operations such as grinding, flotation, thickening, and tailings transport are negatively affected by the presence of clay minerals, which impart complex rheological behaviors to mineral suspensions by increasing their rheological properties. This deterioration arises from specific physicochemical characteristics of clay minerals such as fine particle size, anisotropic character, laminar morphology, and swelling capacity. This work reviews the effects of various rheology-modifying reagents on clay suspensions including kaolinite, illite, and montmorillonite. The reviewed reagents include inorganic salts, pH modifiers, polymers, surfactants, and nanoparticles. Their mechanisms of interaction with solid particles are analyzed, highlighting their influence on the degree of dispersion or aggregation. Furthermore, this review proposes research opportunities focused on the formulation of hybrid reagents, modified biopolymers, and the development of reagents effective under adverse conditions such as high salinity or elevated temperatures. This review provides a comprehensive basis for optimizing the use of rheological additives through more efficient and sustainable strategies for managing clay-rich suspensions in the mining industry.

In the world, the hazards of intense rainfall are recurrent and increasing. In addition, they are one of the natural hazards that cause the most severe damage to infrastructure and even cause deaths every year. Flow-type landslides are capable of develop in areas with different geomorphological, geological and climatic characteristics. In hyper-arid zones such as the Atacama Desert, these hazards are capable of develop in a timely manner, causing catastrophes. This study analyzes the flow-type landslide in a hyper-arid mountainous area in La Chimba basin of Antofagasta city (Chile). For this, a hydrometeorological analysis is carried out through a pluviometric analysis, statistical analysis of frequencies through the Gumbel probabilistic method of extreme values and determination of maximum flows by obtaining IDF (intensity-duration-frequency) curves and design rainfall intensity as a function of concentration time. To obtain the maximum flows of liquid runoff and debris, for different return periods, the rational method was used with the method proposed by O’Brien. For the determination in the impact zone, the modeling software HEC-RAS (Hydrologic Engineering Center’s River Analysis System) and RAMMS (Rapid Mass Movements). Hydrographs are used for a return period of about 200 years, considered the most unfavorable scenario with the Voellmy–Salm model. To validate the modeling, a morphometric, sedimentological and comparative analysis is carried out between real impact zones of 1991 event and those generated in this study. It is concluded that the sedimentological and morphometric characteristics indicate that the type of flow that it can originate would have a rapid response to rainfall events of great intensity or duration. The modeling provided by HEC-RAS represents a fluvial-type flow, while the RAMMS modeling is closer to the consistency of a flow-type landslide, which is estimated to be closer to reality. The results show that despite being in a hyper-arid zone, the rainfall factor is capable of landslides triggering in mountainous areas.