Search

Studying pore networks in rocks is critical for understanding reservoir properties, with mercury intrusion porosimetry (MIP) being a key laboratory method. MIP involves capillary intrusion of mercury, with intrusion pressure (P) related to capillary diameter (d) by the Washburn equation, incorporating mercury properties like contact angle (θ) and surface tension (γ). While a constant contact angle of 140° is typically assumed for MIP, it can vary based on rock mineralogy and surface roughness. This study aims to analyze how contact angle variations and surface roughness affect MIP analysis of carbonate rocks. Initially, contact angle data was obtained for calcite, dolomite, and quartz with varying roughness levels. Synthetic rocks were then constructed using these minerals. MIP was performed using the typical 140° contact angle and a calculated contact angle from the Cassie model, which considers surface composition fraction. Natural rock MIP analysis followed, with contact angles varying due to mineral composition and roughness. The study found higher contact angles than the standard 140°, affecting pore size distributions up to 30%. Natural rock pore network curves were adjusted based on synthetic rock data analysis. These findings emphasize the need for accurate contact angle selection in MIP for precise pore distribution analysis and contribute to the further study of carbonate rocks.

Information about accessibility is of great relevance for gold recovery studies. Obtaining these variables from machine learning models can greatly assist in quickly determining accessibility. Few studies have been published relating the mineralogy of the gold ore process and the application of artificial intelligence, mainly algorithms in predicting variables related to gold recovery and extraction. Accessibility is an important variable for understanding the ability to recover gold from a cyanide solution, which can occur through fractures or some other means that provides access to the solution and consequent leaching of the gold grain. This study aims to present a model capable of predicting the accessibility variable using a data set with 168 characterization results from different ML methods, such as Linear Regression (LR), Random Forest (RF), Sequential Minimum Optimization for Support Vector Machine (SMOreg) and Gaussian Processes (GP). In this context, it was possible to establish that the random forest model performed best by presenting a coefficient of determination R2 (0.77), MAE (11.76), and RMSE (14.48). It was also reported from the SHAP analysis that the Au_grade, exposed_a, and As_grade showed the highest contribution level towards the perdition process of the model.

The demand for critical chemical elements applied in clean energy technologies is increasing and, although deep-sea mining feasibility still is an open question, it might be a pathway to overcome the problem. Among areas of interest for seabed mining, the Rio Grande Rise is an ocean ridge in the southwest Atlantic Ocean known for hosting a large polymetallic mineral deposit containing various critical elements at high concentrations. Therefore, this mineralogical and chemical study characterizes the Rio Grande Rise FeMn crusts and establishes features from a structural-chemical perspective that can guide further studies from various locations. Combining X-ray diffractometry, Raman spectroscopy, chemical analysis, and Scanning Electron Microscopy, it was found that samples are composed by manganese oxides, MnOx; ferryxite or goethite, FeOOH; magnesian calcite, Ca,Mg(CO3)2; and carbonate fluorapatite, Ca5(PO4,CO3)3F. The external portion of analyzed rocks consists of younger crust layers enriched in critical metals, such as cobalt (Co) and nickel (Ni), associated with MnOx – mainly vernadite and asbolane; titanium (Ti), associated with iron oxyhydroxides; and rare earth elements (REE), at distinct bearing minerals. Therefore, the data herein reported show that regions where the FeMn crusts have a thicker young layer host a higher content of critical elements. In addition, the information about the elemental distribution and mineral associations can guide further mineral and metallurgical processing steps.

Few studies have been published on the analysis and correlation of data from process mineralogical studies of gold ore employing artificial neural networks (ANNs). This study aimed to analyse and investigate the correlations obtained by the technological characterization of auriferous ore using an ANN called self-organizing map (SOM) to support geometallurgical studies. The SOM is a data analysis technique in which patterns and relationships within a database are internally derived and the outputs are visual, assisting in the understanding of data in the representation of 2D maps. In the representation generated, it was possible to establish that the variables of accessibility, exposed perimeter, median gold grain diameter (D50), and SiO2 and arsenic contents have strong positive correlations. Regarding geometallurgy, this study shows that SOM can identify large-scale spatial chemical–mineralogical gold ore patterns, which can help define the most relevant indicator variables for mineral processing.

SEM-based automated image analysis is one of the most comprehensive tools in mineralogical characterization and plays an important role in the mining sector, mainly due to its statistical robustness, reliability of results and rapid analysis compared to analogue methods. Mineralogical ore characterization, such as gold distribution, grain size and mode of occurrence, together with density separation, cyanidation and diagnostic leaching tests, are the key for the appropriate process design of the geometallurgy concept. The present research focuses on the development of a mineralogical characterization of low-grade gold ore (4000 ppm) due to a unique set of compositional properties, such as grain size, sulphide mineralogy and accessibility, which directly affect the metallurgical performance. The results demonstrated that there is a direct correlation between the arsenic grades and the gold content, as well as an influence of arsenic grades on gold accessibility. Furthermore, high arsenic content in gold grains tends to provide greater accessibility. Although gold grains occur mainly as inclusions in pyrite and arsenopyrite, they are rarely associated with other sulphide (pyrrhotite and galena).

Sand scarcity is occurring in different countries all over the world as highlighted by the United Nations Environmental Program, therefore, the development of sustainable alternative materials is vital. This paper presents the potential of mineral processing to produce high quality recycled sand by comminuting mixed CDW (Construction and Demolition Waste) into fine fraction at an industrial plant. This methodology represents a change in recycling strategies that proved to be effective for attaining high-quality products that will contribute to enlarge recycled sand market, thus moving toward a circular economy. Samples of mixed CDW were collected from different sources, with different compositions and locations. Primary and secondary crushing were conducted by a jaw crusher, tertiary crushing in a cone crusher and then the material was milled in a rotor impact mill in closed circuit, with 2.0 mm size screening followed by an air classifier to remove the fines (below 0.074 mm). The crushed sand obtained, composed mainly by quartz and feldspar and particles shaped like natural sand, high density (2.71 g/cm3), low water absorption (4.6%) and represents 80% in mass of the recovered fraction. The filler fraction produced, 20% in mass, has a notably higher content of calcium oxide due to the content of cement paste. The sand obtained is particularly distinct from the usually recycled sand generated as a by-product (or mostly tailing), characterized by irregular shape, rough surface and high-water absorption. Appropriate processing is crucial for increasing the waste recycling rates and mitigate the sand scarcity in many world regions.

Abstract This article evaluates the efficiency, benefits and limitations of pre-concentration by density separation for process mineralogy studies of low-grade gold ore. The pre-concentration by density aims to generate a product with a high content of gold and to maximize the number of gold-bearing particles characterized, thereby increasing the representativity and reducing the number of polished sections to be analyzed. Pre-concentration by density was carried out for a low-grade sulfide gold ore (0.96 ppm) from the north of Brazil. The sample was ground to below 1.7 mm, sieved down to 0.037 mm and subjected to density separation, amalgamation of the heavy product and cyanide leaching of all products. Gold was assessed in each product to evaluate the separation recovery and distribution. The finer the particle size, the higher the gold distribution in the heavy product, due to a higher degree of liberation of gold and sulfides; these values varied from 65% to 84% in fractions below 0.60 mm and decreased from 40% to 13% in the coarser fractions. Regarding gold distribution, fractions finer than 0.84 mm indicates a notable increase on gold recovery by amalgamation, indication higher surface exposure.

Brazil has the second largest rare earths mineral (REM) resource in the world, mainly associated with the weathered portion of carbonatite complexes. This paper reports process mineralogy studies performed for 10 samples collected from the deeply weathered portion of different relevant Brazilian deposits, having a soil appearance and varied grain sizes with a significant content of natural fines (below 20 μm). The results indicate that REM are mainly composed of light rare earth elements and present a fine-grained nature and intricate associations with gangue minerals. Monazite is by far the most relevant REM; cerianite and bastnaesite are typical of only one of the studied deposits. The complexity of the occurrence of the rare earths challenges the development of mineral processing routes. A scandium phosphate mineral identified as a trace in one of the studied deposits has not yet been reported in the Brazilian alkaline complexes.

Feldspars are used as a fluxing agent in ceramics and glass production. However, the presence of iron-bearing minerals reduces whiteness of the ceramics. The objective of this work was to decrease the Fe2O3 content of a foyaite to

This paper compares the use of jaw and impact secondary crushing for producing coarse recycled aggregates from concrete wastes, obtained from road pavement and demolished building materials. The crushing mechanism interferes directly with recycled aggregate properties at different levels: particle size distribution, aggregate shape, generation of micro-fractures, as well as regarding the detachment of porous hardened cement paste from particle surface in order to recover pure, non-porous natural aggregates. However, crusher selection in the recycling industry is mostly carried out by acquisition and maintenance costs, industry and manufacturer traditional habits, low cost associated with second hand equipment. It also does not consider essential parameters such as the final properties of the desired end-product. Representative samples from two recycling plants were collected after primary impact crusher and secondary crushing were performed in a controlled laboratory condition through jaw and impact crushers. The aggregates attained were characterized, demonstrating similar density, porosity, particle size distribution and content of attached cement paste. Minor observed differences do not justify the common belief in the industry that impact crushers provide an improvement in the quality of recycled aggregates due to the higher detachment of cement paste from aggregates. Keywords: Recycled concrete aggregate, Liberation comminution, Recycled aggregate properties, Impact crusher, Jaw crusher