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Mineralogy and Geochemistry of Listvenite-Hosted Ni–Fe Sulfide Paragenesis—A Case Study from Janjevo and Melenica Listvenite Occurrences (Kosovo)
Inferring the Orientations of the Foliation and Lineation Defined by Quartz c-Axis Fabrics: Methods and Applications
Reviving Riches: Unleashing Critical Minerals from Copper Smelter Slag Through Hybrid Bioleaching Approach
Geochemical Dynamics and Evolutionary Implications of Sediments at the Xingu–Amazon Rivers’ Confluence: Proxies for Mixing, Mobility and Weathering
3D Inversion and Interpretation of Airborne Multiphysics Data for Targeting Porphyry System, Flammefjeld, Greenland

Journal Description

Minerals

Minerals is an international, peer-reviewed, open access journal of natural mineral systems, mineral resources, mining, and mineral processing. Minerals is published monthly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), GeoRef, CaPlus / SciFinder, Inspec, Astrophysics Data System, AGRIS, and other databases.
Journal Rank: JCR - Q2 (Mineralogy) / CiteScore - Q2 (Geology)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 18 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion journal: Mining

Impact Factor: 2.2 (2023); 5-Year Impact Factor: 2.5 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2075-163X

Latest Articles

18 pages, 2790 KiB

Open AccessArticle

Particle Size-and Structure-Dependent Breakage Behaviors of EnAM-Containing Slags

by Simon Bahnmüller, Paul Hirschberger, Thu Trang Võ, Cindytami Rachmawati, Arno Kwade, Urs Peuker, Harald Kruggel-Emden and Carsten Schilde

Minerals 2025, 15(2), 195; https://doi.org/10.3390/min15020195 - 19 Feb 2025

Slags containing critical minerals concentrated in artificial phases, so-called engineered artificial minerals (EnAMs), are a novel source of critical raw materials. To liberate the EnAMs, the slags need to be comminuted, reducing the size of the particles. This work investigated the dependence of [...] Read more.

Slags containing critical minerals concentrated in artificial phases, so-called engineered artificial minerals (EnAMs), are a novel source of critical raw materials. To liberate the EnAMs, the slags need to be comminuted, reducing the size of the particles. This work investigated the dependence of the breakage behavior on particle size and mineral structure during the comminution of an EnAM-containing slag. Piston-die experiments were performed for particles in the 3 mm to 5 mm size range. Nanoindentation and two-roller breakage tester experiments were performed for those in the 50 µm to 200 µm size range. The investigations were accompanied by X-ray computed tomography (XCT) and scanning electron microscope/energy dispersive X-ray spectroscopy (SEM/EDX) measurements as well as a micro X-ray fluorescence analysis to examine the mineral microstructure. It was found that the commonly assumed exponential connection between particle size and strength differed in the two size ranges. This behavior can be linked to different grain and cluster sizes, which were found in the investigation of the mineral microstructure. In addition to particle size, it was found that mineral structure plays an important role when characterizing the breakage behavior. Full article

(This article belongs to the Collection Engineered Artificial Minerals (EnAMs): A Geo-Metallurgical Tool to Recycle Critical Elements from Waste Streams: Synthesis, Characterization, Metallurgical and Mechanical Processing (SPP 2315))

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Figure 1
<p>(<b>a</b>) A part of the homogeneous structure shown in element map overlay from micro X-ray fluorescence analysis and (<b>b</b>) the binary image of the observed clusters.</p> Full article ">Figure 2
<p>Representative schematic representation of the structures: mineral grains and clusters in the slag sample are shown for three exemplary clusters, where a single hexagonal shape represents a single mineral grain and the accumulation of the connected single grains forms a cluster.</p> Full article ">Figure 3
<p>Three-dimensional visualization of XCT data of three clusters consisting of smaller grains. Every grain is labelled with a unique color for easier differentiation.</p> Full article ">Figure 4
<p>Size distributions of the determined grain size determined based on XCT image data (<b>a</b>) and the cluster size based on µXRF imaging (<b>b</b>) of the analyzed slag.</p> Full article ">Figure 5
<p>SEM (<b>a</b>,<b>b</b>) and SEM/EDX (<b>c</b>,<b>d</b>) images of two samples (<b>a</b>–<b>d</b>) in the micro size range to investigate the structural composition on the surface.</p> Full article ">Figure 6
<p>Side view of the load cell (Shimadzu AG-50kNX) during the piston tests (<b>a</b>) and a schematic representation of the load cell’s setup (<b>b</b>).</p> Full article ">Figure 7
<p>Schematic representation of the two-roller breakage tester.</p> Full article ">Figure 8
<p>Distribution of the breakage strength of particles in different size classes in the micro and macro size ranges.</p> Full article ">Figure 9
<p>The specific breakage strength as a function of particle size, fitted based on the model by Tavares and King [<a href="#B33-minerals-15-00195" class="html-bibr">33</a>]. Grain and cluster sizes are highlighted as vertical lines.</p> Full article ">Figure 10
<p>Normalized fragment size distribution in the micro and macro size ranges and normalized cluster and grain size distributions.</p> Full article ">Figure 11
<p>Normalized fragment size distributions in the micro and macro ranges and fits for the breakage function by Zhu et al. [<a href="#B42-minerals-15-00195" class="html-bibr">42</a>].</p> Full article ">

17 pages, 4237 KiB

Open AccessArticle

Prediction of Mine Waste Rock Drainage Quantity Using a Machine Learning Model with Physical Constraints

by Can Zhang, Liang Ma and Wenying Liu

Minerals 2025, 15(2), 194; https://doi.org/10.3390/min15020194 - 19 Feb 2025

Mining activities generate substantial amounts of waste rock, which are often disposed of in waste rock piles. Drainage from these piles can pose serious environmental risks. It is crucial to reliably predict drainage properties in order to effectively manage them. In previous work, [...] Read more.

Mining activities generate substantial amounts of waste rock, which are often disposed of in waste rock piles. Drainage from these piles can pose serious environmental risks. It is crucial to reliably predict drainage properties in order to effectively manage them. In previous work, we developed a machine learning model to predict waste rock drainage quantity using weather monitoring data as the input and drainage flow rate as the output. However, this model lacked physical constraints, limiting its interpretability, reliability, and applicability. In this study, we introduced a new machine learning model designed with physical constraints to improve the predictions of drainage quantity. This new model incorporates a weather refining sub-model and integrates physical constraints to enhance the overall reliability of the model predictions. The weather refining sub-model transforms primary weather features (total precipitation and temperature) into secondary features (rainfall, snowmelt, and evaporation) through established mathematical relationships. These secondary features were then used as inputs for the machine learning model to predict drainage quantity. To embed physical principles within the machine learning model, we integrated a water balance equation into the neural network architecture and modified the loss function accordingly. In addition, we included an adjustable bias term to optimize the balance between model performance and interpretability. Compared with our previous model, the incorporation of physical constraints into the machine learning model improved the accuracy of the drainage quantity predictions. More importantly, this approach ensures that the model outputs adhere to physical laws, thereby enhancing its interpretability, reliability, and applicability. Full article

(This article belongs to the Section Environmental Mineralogy and Biogeochemistry)

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<p>A schematic of methodology developed in the present study for simulating waste rock drainage quantity.</p> Full article ">Figure 2
<p>A schematic of the neural network structure design for the drainage quantity model.</p> Full article ">Figure 3
<p>Comparison of model outputs and measured drainage flow rates during model training and testing for (<b>a</b>) Station 1; (<b>b</b>) Station 2; and (<b>c</b>) Station 3.</p> Full article ">Figure 3 Cont.
<p>Comparison of model outputs and measured drainage flow rates during model training and testing for (<b>a</b>) Station 1; (<b>b</b>) Station 2; and (<b>c</b>) Station 3.</p> Full article ">Figure 4
<p>The monthly contribution of the bias term to the drainage quantity prediction for the three drainage monitoring stations studied.</p> Full article ">Figure 5
<p>Comparison of the sensitivity test results (one involving increasing the temperature and the other involving increasing the total precipitation) with the original predictions of the test sets for (<b>a</b>) Station 1; (<b>b</b>) Station 2; and (<b>c</b>) Station 3.</p> Full article ">Figure 6
<p>Non-negative monotonicity means that all data points are positioned along or above the diagonal line. (<b>a</b>) Monotonicity test results for the drainage quantity model with the physical loss term in the loss function; (<b>b</b>) Monotonicity test results for the drainage quantity model without the physical loss term in the loss function.</p> Full article ">Figure 7
<p>The decrease in the NSE scores of the test sets with an increasing number of lag days for the three drainage monitoring stations.</p> Full article ">Figure 8
<p>Comparison of the drainage flow rates predicted by the original model, predicted by the model with three lag days, and the observed values of the test set of Station 1.</p> Full article ">

17 pages, 3450 KiB

Open AccessArticle

Research on Optimization of Lifter of an SAG Mill Based on DEM Simulation and Orthogonal Tests and Applications

by Guobin Wang, Qingfei Xiao, Xiaojiang Wang, Yunxiao Li, Saizhen Jin, Mengtao Wang, Yunfeng Shao, Qian Zhang, Yingjie Pei and Ruitao Liu

Minerals 2025, 15(2), 193; https://doi.org/10.3390/min15020193 - 19 Feb 2025

The unreasonable parameters of mill liner lifter bars will not only decrease the operating rate of the mill and increase electricity consumption but, also, seriously restrict the production capacity of the mill. Therefore, optimizing the parameters of liner lifter bars is helpful to [...] Read more.

The unreasonable parameters of mill liner lifter bars will not only decrease the operating rate of the mill and increase electricity consumption but, also, seriously restrict the production capacity of the mill. Therefore, optimizing the parameters of liner lifter bars is helpful to save energy, improve its production capacity, and increase benefits for enterprises. Given the unreasonable parameters of the lifter bars of the semi-autogenous grinding (SAG) mill in a beneficiation plant in Yunnan (China), the distinct element method (DEM) with orthogonal tests was used to conduct simulation, the simulation results demonstrating that the three parameters all had significant influence on the collision energy, with the order of group numbers > angles > heights by the analysis of range and variance, and the optimal parameters combination, with angles of 20°, groups of 12, and heights of 210 mm, was obtained. Then, the lifer bars optimized were applied in industrial tests to verify their effect, and the results illustrated that all of the service life of lifter bars, the operating rate, production capacity, and electricity consumption were significantly improved at 159 days, 92.32%, 54.37 t/h, and 21.45 kW·h/t, respectively. This paper proposes a reference for the similar design and optimization of lifter bars for the other beneficiation plants. Full article

(This article belongs to the Special Issue Recent Advances in Ore Comminution)

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<p>Fraction composition of SAG mill feed.</p> Full article ">Figure 2
<p>Fraction composition of SAG mill discharge.</p> Full article ">Figure 3
<p>Results of mechanical properties of ores.</p> Full article ">Figure 4
<p>Main view of cylinder liner of SAG mill with the diameter of 5.5 m.</p> Full article ">Figure 5
<p>Schematic diagram of contact model. (<b>a</b>) Schematic diagram of contact between particles (<b>b</b>) Contact model of Hertz Mindlin.</p> Full article ">Figure 6
<p>Model of steel balls (<b>left</b>) and ore (<b>right</b>).</p> Full article ">Figure 7
<p>Movement states of materials inside an SAG mill with different parameters.</p> Full article ">Figure 8
<p>The operating rate of the SAG mill before and after the lifter bars were optimized.</p> Full article ">Figure 9
<p>The production efficiency of the SAG mill before and after the lifter bars were optimized.</p> Full article ">Figure 10
<p>The electricity consumption of the SAG mill before and after the lifter bars were optimized.</p> Full article ">

27 pages, 11125 KiB

Open AccessArticle

Geochemical Insights and Mineral Resource Potential of Rare Earth Elements (REE) in the Croatian Karst Bauxites

by Erli Kovačević Galović, Nikolina Ilijanić, Nikola Gizdavec, Slobodan Miko and Zoran Peh

Minerals 2025, 15(2), 192; https://doi.org/10.3390/min15020192 - 19 Feb 2025

Karst bauxites are valuable terrestrial records of paleoclimate and tectonic evolution formed under tropical to subtropical conditions during the subaerial exposure of carbonate platforms. This study explores Croatian bauxite deposits within the Adriatic–Dinaric Carbonate Platform (ADCP), with a focus on the distribution and [...] Read more.

Karst bauxites are valuable terrestrial records of paleoclimate and tectonic evolution formed under tropical to subtropical conditions during the subaerial exposure of carbonate platforms. This study explores Croatian bauxite deposits within the Adriatic–Dinaric Carbonate Platform (ADCP), with a focus on the distribution and enrichment of rare earth elements (REE) across eight bauxite horizons from the Triassic to Neogene periods. The research applies statistical analyses of geochemical data, as well as developed models, to assess the factors influencing REE distribution and fractionation. The study found that variations in parent material, along with changes in paleogeographical and paleotectonic settings, significantly affected the REE content. The median REE concentrations in the analyzed bauxite horizons range from approximately 250 to 570 mg/kg. Notable REE enrichment was observed in the Late Paleogene, particularly in the Middle and Upper Eocene horizons. The analysis highlights the importance of physicochemical conditions, such as Eh and pH, during the weathering processes that lead to bauxite formation. The results suggest that the presence of REE-bearing minerals, rather than clay minerals, could possibly contribute to elevated concentrations of heavy REE (HREE). These findings indicate that Croatian bauxites, enriched in REE and associated trace elements, are significant not only as geological markers of past climatic and tectonic events but also as potential sources of critical raw materials. This study underscores the potential for the economic exploitation of these deposits in the context of modern technological demands. Full article

(This article belongs to the Special Issue Trace Elements in Bauxite Deposits: Critical Georesource and Significant Indicators of Paleoenvironmental Conditions)

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<p>(<b>a</b>) Deposits and occurrences of bauxites in Croatia (red dots; source: Map of Mineral Resources of the Republic of Croatia, Croatian Geological Survey) [<a href="#B45-minerals-15-00192" class="html-bibr">45</a>] within Adriatic (yellow area) and Dinaric (green area) units in Croatian karst Dinarides. (<b>b</b>) Geographical position of External Dinarides in the Republic of Croatia (orange area). The numbers represent seven subregions of the Republic of Croatia: 1. Banovina and Kordun, 2. Istrian peninsula, 3. Kvarner coast and Velebit foothill, 4. Lika, 5. Northern Dalmatia, 6. Central Dalmatia, and 7. Southern Dalmatia.</p> Full article ">Figure 2
<p>Stratigraphic positions of bauxite-bearing horizons in the schematic representation of the Croatian karst Dinarides: BX1 Upper Triassic, BX2 Upper Jurassic, BX3 Lower Cretaceous, BX4 Upper Cretaceous, BX5 Paleocene, BX6 Middle Eocene, BX7 Upper Eocene, and BX8 Miocene. Modified from [<a href="#B42-minerals-15-00192" class="html-bibr">42</a>].</p> Full article ">Figure 3
<p>Locations of the sampled bauxite deposits from eight bauxite-bearing horizons from the Upper Triassic to the Miocene (BX1–BX8) in the study area (Croatian karst Dinarides).</p> Full article ">Figure 4
<p>Diagram showing median values of ΣLREE, ΣHREE, and ΣREE in the Croatian karst bauxite horizons (BX1–BX8).</p> Full article ">Figure 5
<p>Median REE values (including Sc and Y) in the Croatian karst bauxite horizons (BX1–BX8).</p> Full article ">Figure 6
<p>Box-and-whisker plots showing abundances of REE elements (including Sc and Y), LREE, HREE, and ΣREE (displayed in mg/kg) in the Croatian karst bauxite horizons. The plots represent univariate statistics of geochemical data (descriptor variables min–max, median, and first and third quartile values) for each bauxite horizon (BX1–BX8).</p> Full article ">Figure 7
<p>REE patterns for median values from the Croatian karst bauxite horizons (BX1–BX8) normalized to (<b>a</b>) chondrite and (<b>b</b>) upper continental crust. The normalization factors are from [<a href="#B55-minerals-15-00192" class="html-bibr">55</a>] (chondrite) and [<a href="#B60-minerals-15-00192" class="html-bibr">60</a>] (UCC).</p> Full article ">Figure 8
<p>Comparison of La/Y and ΣLREE/ΣHREE value curves for median values in the Croatian karst bauxite horizons.</p> Full article ">Figure 9
<p>Median REE fractionation ratios for the Croatian karst bauxite horizons (BX1–BX8).</p> Full article ">Figure 10
<p>Variation in Ce-anomalies, Eu-anomalies, and La/Y ratios for the Croatian karst bauxite horizons (BX1–BX8). The values represent the median values for a particular horizon.</p> Full article ">Figure 11
<p>(<b>a</b>) Eu/Eu* and TiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> binary diagram (modified after [<a href="#B28-minerals-15-00192" class="html-bibr">28</a>]). (<b>b</b>) Eu/Eu* vs. Sm/Nd binary diagram showing mixing lines between average standard lithologies. Modified after [<a href="#B56-minerals-15-00192" class="html-bibr">56</a>]. Colored circles represent the median values of the Croatian karst bauxite horizons (BX1–BX8).</p> Full article ">Figure 12
<p>Binary diagram of Cr vs. Ni showing the median composition of the bauxite horizons relative to other Mediterranean karst bauxite deposits represented as average values and standard deviations. Colored circles represent the median values of the Croatian karst bauxite horizons (BX1–BX8). Colored stars represent median values of Montenegrin bauxite from four stratigraphic horizons [<a href="#B36-minerals-15-00192" class="html-bibr">36</a>] (modified after [<a href="#B28-minerals-15-00192" class="html-bibr">28</a>]).</p> Full article ">Figure 13
<p>Binary diagram showing the concentration of Cr vs. Ni in laterite- and karst-type bauxites and potential precursor rocks. Colored circles represent median values of the Croatian karst bauxite horizons (BX1–BX8) (modified after [<a href="#B75-minerals-15-00192" class="html-bibr">75</a>]).</p> Full article ">Figure 14
<p>Comparison between variables and Croatian karst bauxite horizons in the discriminant function model (DFM) of the clr-transformed data: scatterplots of (<b>a</b>) variable loadings and (<b>b</b>) bauxite horizons in the reduced discriminant space of the first two discriminant functions (DF1–DF2).</p> Full article ">Figure 15
<p>(<b>a</b>) Distribution of bauxite deposit groups in Central Dalmatia, (<b>b</b>) detailed density of individual deposits (source: Map of Mineral Resources of the Republic of Croatia, Croatian Geological Survey) [<a href="#B45-minerals-15-00192" class="html-bibr">45</a>].</p> Full article ">

18 pages, 11606 KiB

Open AccessArticle

Influence of Tectonic Setting and Sedimentary Environment on Organic-Rich Shale in the Wufeng Formation, Fenggang Area

by Qian Zhang, Haiquan Zhang, Yupeng Men, Qian Yu, Junfeng Cao, Yexin Zhou, Xintao Feng, Ankun Zhao and Daorong Zhou

Minerals 2025, 15(2), 191; https://doi.org/10.3390/min15020191 - 19 Feb 2025

Drawing on extensive geological surveys, as well as systematic mineralogical, petrological, and geochemical analyses, the study evaluates the provenance, tectonic setting, paleo-redox conditions, and paleoclimate characteristics of the Wufeng Formation black shale in the Fenggang area. The analysis of mineral components reveals that [...] Read more.

Drawing on extensive geological surveys, as well as systematic mineralogical, petrological, and geochemical analyses, the study evaluates the provenance, tectonic setting, paleo-redox conditions, and paleoclimate characteristics of the Wufeng Formation black shale in the Fenggang area. The analysis of mineral components reveals that quartz content is notably the highest, suggesting that the shale is primarily siliceous. The TOC content was highest in the YI Outcrop, ranging from 2.19 to 5.56, with an average of 3.23, followed by the SX Outcrop. Redox-sensitive indices including Mo_EF, U_EF, V/Cr, and U/Th exhibit considerable variability, indicating significant heterogeneity of the redox conditions, which is primarily characterized as a restricted marine shelf setting. The bottom water of YI Outcrop has the strongest reducing property, and mainly deposited in an anoxic environment. Organic-rich siliceous mudstone is widely distributed across the region. The provenance analysis indicates that the study area is predominantly sourced from felsic igneous rocks. Additionally, paleoclimate and paleo-weathering analyses suggest that the region underwent intense chemical weathering under warm climatic conditions. We found that the sedimentary environment exhibits pronounced spatial variability. In the northern part of the study area, water conditions were deeper, anoxic, and reducing. Toward the east, water depth gradually decreased, transitioning to weakly oxidizing and suboxic conditions. Furthermore, significant tectonic activity in the region led to the formation of multiple underwater highs, indicative of an active continental margin likely associated with the rapid uplift of paleo-uplifts. The formation of organic-rich shale was primarily influenced by two factors: favorable preservation conditions in reducing water bodies and high primary productivity driven by biological activity in weakly oxic environments. Full article

(This article belongs to the Special Issue Element Enrichment and Gas Accumulation in Black Rock Series)

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<p>Study area location and sedimentary facies map. (<b>a</b>) The overall outline of the Upper Yangtze plate in the Late Ordovician; (<b>b</b>) the location of the study area and its distribution in the upper Yangtze plate; (<b>c</b>) sedimentary facies map and sampling point location of the Wufeng Formation during the depositional period in the study area.</p> Full article ">Figure 2
<p>(<b>a</b>) Graptolite characteristics in the YI Outcrop; (<b>b</b>) Hirnantian brachiopods from the Guanyinqiao Formation in the WL Outcrop; (<b>c</b>) siliceous shale in the Wufeng Formation of the YI Outcrop, as observed in thin sections; (<b>d</b>) organic matter in the YI Outcrop, as observed under a scanning electron microscope (SEM); (<b>e</b>) strawberry-shaped pyrite in the SX Outcrop, partially filling organic matter, as observed under SEM; (<b>f</b>) development of organic matter pores in the Wufeng Formation of the WL Outcrop, as observed under SEM.</p> Full article ">Figure 3
<p>Comparison of mineral composition (<b>a</b>) and (<b>b</b>) triangular diagram of lithofacies division in the study area.</p> Full article ">Figure 4
<p>Linear diagram of terrigenous material input. Cross-plot of (<b>a</b>) Al<sub>2</sub>O<sub>3</sub> vs. TiO<sub>2</sub>, (<b>b</b>) Al<sub>2</sub>O<sub>3</sub> vs. Ti/Al, and (<b>c</b>) Al<sub>2</sub>O<sub>3</sub> vs. SiO<sub>2</sub>.</p> Full article ">Figure 5
<p>Diagrams for hydrothermal genesis identification. (<b>a</b>) Zn-Ni-Co ternary diagram [<a href="#B27-minerals-15-00191" class="html-bibr">27</a>]; (<b>b</b>) Eu/Sm-Sm/Yb discrimination diagram [<a href="#B28-minerals-15-00191" class="html-bibr">28</a>].</p> Full article ">Figure 6
<p>The source rock discrimination diagrams for mudstone. (<b>a</b>,<b>b</b>) base from Condie, KC [<a href="#B31-minerals-15-00191" class="html-bibr">31</a>].</p> Full article ">Figure 7
<p>Provenance attribute (<b>a</b>,<b>b</b>) and sedimentary tectonic background (<b>c</b>,<b>d</b>) discriminant map. The base map is modified from Roser and Korsch (1988) [<a href="#B32-minerals-15-00191" class="html-bibr">32</a>], Roser and Korsch (1986) [<a href="#B33-minerals-15-00191" class="html-bibr">33</a>], Bhatia MR. (1985) [<a href="#B34-minerals-15-00191" class="html-bibr">34</a>] and Zhang et al. (2023) [<a href="#B16-minerals-15-00191" class="html-bibr">16</a>], respectively.</p> Full article ">Figure 8
<p>Comparison of oxidation-reduction properties in the study area; (<b>a</b>,<b>b</b>) are based on Zhang et al. (2023) [<a href="#B16-minerals-15-00191" class="html-bibr">16</a>] and Algeo and Tribovillard (2009) [<a href="#B39-minerals-15-00191" class="html-bibr">39</a>]; (<b>c</b>,<b>d</b>) are based on Algeo and Lyons (2006) [<a href="#B25-minerals-15-00191" class="html-bibr">25</a>] and Zhou et al. (2015) [<a href="#B36-minerals-15-00191" class="html-bibr">36</a>].</p> Full article ">Figure 9
<p>A-CN-K diagrams on both sides of the ancient land (<b>a</b>) and CIA diagrams (<b>b</b>) [<a href="#B39-minerals-15-00191" class="html-bibr">39</a>]. PAAS, post-Archean Australian shales [<a href="#B20-minerals-15-00191" class="html-bibr">20</a>]; UCC, upper-crust rocks [<a href="#B20-minerals-15-00191" class="html-bibr">20</a>].</p> Full article ">Figure 10
<p>Analysis of paleoproductivity (<b>a</b>,<b>b</b>) and main controlling factors of organic matter enrichment (<b>c</b>,<b>d</b>) in study area.</p> Full article ">Figure 11
<p>Organic matter enrichment model of Wufeng Formation shale in the Fenggang Area.</p> Full article ">

25 pages, 85884 KiB

Open AccessArticle

Petrogenesis and Geological Implications of the Qiaoqi Intrusion in Western Margin of the Yangtze Block, SW China: Evidence from Geochronology, Geochemistry, and Hf Isotopes

by Yingtao Chen, Jianting Zhu, Shaoni Wei, Xiaochen Zhao, Delu Li, Xufeng Yang and Yuhang Wang

Minerals 2025, 15(2), 190; https://doi.org/10.3390/min15020190 - 19 Feb 2025

Late Permian–Early Triassic basic rocks, which are widespread in the western margin of the Yangtze block (SW China), provide critical information for regional tectonic evolution. The Qiaoqi intrusion, distributed in the western margin of the Yangtze block, is selected as a representative for [...] Read more.

Late Permian–Early Triassic basic rocks, which are widespread in the western margin of the Yangtze block (SW China), provide critical information for regional tectonic evolution. The Qiaoqi intrusion, distributed in the western margin of the Yangtze block, is selected as a representative for discussion in this paper. LA-ICP-MS zircon U-Pb dating results show that the Qiaoqi intrusion was formed at 245 ± 1 Ma. It belongs to the medium-K calc-alkaline and tholeiitic basalt series. It is characterized by high concentrations of Fe₂O₃^T (11.53 wt. % to 15.50 wt. %), TiO₂ (1.81 wt. % to 3.20 wt. %), Al₂O₃ (11.80 wt. % to 15.60 wt. %), and low concentrations of MgO (4.51 wt. % to 8.93 wt. %). The LREE and LILE (such as Cs, Rb, Ba and Th) are enriched, with insignificant Eu anomalies (Eu/Eu* = 0.92 to 1.13). The chondrite-normalized REE distribution diagram shows a right-leaning pattern, similar to ocean island basalts (OIB), displaying the geochemical characteristics of enriched mantle sources. The zircon εHf(t) values are relatively high (+12.7 to +15.5) and the single-stage Hf model ages are relatively young (t_DM = 272 to 386 Ma). Modeling further reveals that the parent magma was derived from 13% to 19% partial melting of garnet peridotite. Comprehensive analysis shows that the geochemical characteristics of the Qiaoqi intrusion bear resemblance to those of the Emeishan basalts, which are attributed to volumetrically minor melting of the fossil Emeishan plume head beneath the Yangtze crust following the eruption of the Emeishan Large Igneous Province (ELIP). This understanding further constrains the duration of the Emeishan Large Igneous Province and provides new support for understanding the formation, evolution and distribution of the Emeishan Large Igneous Province. Full article

(This article belongs to the Section Mineral Geochemistry and Geochronology)

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<p>(<b>a</b>,<b>b</b>) Map showing geology of the Emeishan Large Igneous Province (modified after [<a href="#B29-minerals-15-00190" class="html-bibr">29</a>]).</p> Full article ">Figure 2
<p>(<b>a</b>) The geological section of the Qiaoqi intrusion. (<b>b</b>–<b>d</b>) The outcrops of the Qiaoqi intrusion. (<b>b</b>) The contact part of the intrusion and the surrounding rock is squeezed and deformed by tectonic activity. (<b>c</b>) The surrounding rock is deformed by the extrusion of the front edge of the magmatic bedding intrusion. (<b>d</b>) The gabbro and the surrounding rock into bedding intrusion contact. D<sub>3</sub>C<sub>1</sub><span class="html-italic">m</span> represents Maoba Formation limestone, βμ represents gabbro.</p> Full article ">Figure 3
<p>Microphotographs of the Qiaoqi intrusion. (<b>a</b>) Gabbro with plagioclase, clinopyroxene, amphibole, cross-polarized light. (<b>b</b>) Clinopyroxene with twin structure, cross-polarized light. (<b>c</b>) Amphibole replaced by magnetite, cross-polarized light. (<b>d</b>) Gabbro with pyroxene structure, cross-polarized light. (Cpx: clinopyroxene, Pl: plagioclase, Amph: amphibole, Mgt: magnetite).</p> Full article ">Figure 4
<p>Classification diagrams of the Qiaoqi intrusion. (<b>a</b>) Total alkali vs. silica (TAS) diagram (after [<a href="#B47-minerals-15-00190" class="html-bibr">47</a>]). (<b>b</b>) Potassium vs. silica diagram (after [<a href="#B48-minerals-15-00190" class="html-bibr">48</a>]). The data of Emeishan basalts are from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 5
<p>(<b>a</b>) Chondrite-normalized REE distribution patterns and (<b>b</b>) primitive mantle-normalized multi-element diagram of the Qiaoqi intrusion. Normalized values for chondrite and primitive mantle are from [<a href="#B51-minerals-15-00190" class="html-bibr">51</a>] and [<a href="#B49-minerals-15-00190" class="html-bibr">49</a>], respectively. The shaded areas show ranges of the typical Emeishan basalts, data from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 6
<p>Representative CL images of zircons showing apparent <sup>206</sup>Pb/<sup>238</sup>U ages, concordia diagrams for zircon and weighted mean ages diagram from the Qiaoqi intrusion. Solid yellow circles are U-Pb dating positions and dashed yellow circles are Hf isotope analysis positions. (<b>a</b>) S1-2; (<b>b</b>) S1-4; (<b>c</b>) S2-2.</p> Full article ">Figure 7
<p>Plots of εHf(t) vs. U-Pb age for zircons from the Qiaoqi intrusion (after [<a href="#B59-minerals-15-00190" class="html-bibr">59</a>]). Data for ELIP from [<a href="#B60-minerals-15-00190" class="html-bibr">60</a>] also presented for comparison.</p> Full article ">Figure 8
<p>Harker diagrams for the Qiaoqi intrusion.</p> Full article ">Figure 9
<p>(<b>a</b>) La/Sm vs. La diagram and (<b>b</b>) La/Nb vs. SiO<sub>2</sub> diagram for the Qiaoqi intrusion (after [<a href="#B64-minerals-15-00190" class="html-bibr">64</a>,<a href="#B65-minerals-15-00190" class="html-bibr">65</a>]). The data of Emeishan basalts are from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 10
<p>(<b>a</b>) La/Yb vs. Nb/Yb diagram for the Qiaoqi intrusion (after [<a href="#B76-minerals-15-00190" class="html-bibr">76</a>]). (<b>b</b>) Ta/Yb vs. Nb/Yb diagram for the Qiaoqi intrusion (after [<a href="#B76-minerals-15-00190" class="html-bibr">76</a>]). (<b>c</b>) Th/Yb vs. Ta/Yb diagram for the Qiaoqi intrusion (after [<a href="#B77-minerals-15-00190" class="html-bibr">77</a>]). Vectors indicate the influence of subduction components (S), within-plate enrichment (W), crustal contamination (C), and fractional crystallization (F). Dashed lines separate the boundaries of the tholeiitic (TH), calc-alkaline (CA), and shoshonitic (SHO) fields. Values of N-MORB, E-MORB, OIB, and WPB are from [<a href="#B49-minerals-15-00190" class="html-bibr">49</a>]. The data of Emeishan basalts are from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 11
<p>(<b>a</b>) La/Sm vs. Sm/Yb plot (after [<a href="#B81-minerals-15-00190" class="html-bibr">81</a>]) for the Qiaoqi intrusion, PM—primary mantle [<a href="#B82-minerals-15-00190" class="html-bibr">82</a>]; DMM—depleted mantle [<a href="#B82-minerals-15-00190" class="html-bibr">82</a>]. (<b>b</b>) Sm/Yb vs. La/Yb plot for the Qiaoqi intrusion (after [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>]). The data of Emeishan basalts are from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 12
<p>(<b>a</b>) AFM diagram for the Qiaoqi intrusion (after [<a href="#B84-minerals-15-00190" class="html-bibr">84</a>]). (<b>b</b>) Ti/100-Zr-Y*3 diagram for the Qiaoqi intrusion (after [<a href="#B85-minerals-15-00190" class="html-bibr">85</a>]), WPB: within-plate basalts, IAT: island-arc tholeiites, CAB: calc-alkaline basalts, MORB: mid-ocean ridge basalts. (<b>c</b>) Zr/Y vs. Zr diagram for the Qiaoqi intrusion (after [<a href="#B86-minerals-15-00190" class="html-bibr">86</a>]), IAB: island-arc basalts. (<b>d</b>) Th/Hf vs. Ta/Hf diagram for the Qiaoqi intrusion (after [<a href="#B83-minerals-15-00190" class="html-bibr">83</a>]), I—plate divergent margin MORB; II—margin of convergent plate (II<sub>1</sub>—island are of continental margin; II<sub>2</sub>—volcanic are of continental margin); III—oceanic intra plate (the oceanic island and seamount, T-MORB, E-MORB); IV—continental intraplate (IV<sub>1</sub>—continental rift + continental margin rift tholeiites; IV<sub>2</sub>—alkaline basalt zone; IV<sub>3</sub>—tensional zone); V—mantle plume. The data of Emeishan basalts are from [<a href="#B18-minerals-15-00190" class="html-bibr">18</a>].</p> Full article ">Figure 13
<p>Histogram of zircon U-Pb ages for ELIP (data sources: [<a href="#B16-minerals-15-00190" class="html-bibr">16</a>,<a href="#B18-minerals-15-00190" class="html-bibr">18</a>,<a href="#B23-minerals-15-00190" class="html-bibr">23</a>,<a href="#B28-minerals-15-00190" class="html-bibr">28</a>,<a href="#B29-minerals-15-00190" class="html-bibr">29</a>,<a href="#B60-minerals-15-00190" class="html-bibr">60</a>,<a href="#B88-minerals-15-00190" class="html-bibr">88</a>,<a href="#B89-minerals-15-00190" class="html-bibr">89</a>,<a href="#B90-minerals-15-00190" class="html-bibr">90</a>,<a href="#B91-minerals-15-00190" class="html-bibr">91</a>,<a href="#B92-minerals-15-00190" class="html-bibr">92</a>,<a href="#B96-minerals-15-00190" class="html-bibr">96</a>]).</p> Full article ">

17 pages, 5546 KiB

Open AccessArticle

Sulfuric Acid Leaching of Ionic Rare Earth Magnesium Salt Enrichment and Removing Aluminum by MgO Precipitation

by Qiang Wang, Tao Qi, Yinliang Liu, Hongdong Yu, Limin Zhang and Wei Zhan

Minerals 2025, 15(2), 189; https://doi.org/10.3390/min15020189 - 18 Feb 2025

Production of rare earth enrichment from the in situ leaching solution of ion-adsorbed rare earth ores greatly decreases the treatment scale and significantly reduces production energy consumption and cost. However, the generated rare earth enrichment has a high content of impurities. Further purification [...] Read more.

Production of rare earth enrichment from the in situ leaching solution of ion-adsorbed rare earth ores greatly decreases the treatment scale and significantly reduces production energy consumption and cost. However, the generated rare earth enrichment has a high content of impurities. Further purification of rare earth is necessary. Therefore, a process comprised of sulfuric acid leaching and removing aluminum by the neutralization precipitation method to obtain the purified rare earth solution was proposed. The results of acid leaching revealed that at a sulfuric acid concentration of 1.75 mol/L, a temperature of 60 °C, a liquid–solid ratio of 5:1 mL/g, a leaching time of 0.5 h, and a stirring rate of 300 r/min, leaching efficiency of rare earth and magnesium reached 99.11% and 97.39%, respectively, while the leaching efficiencies of aluminum and silicon reached 72.91% and 55.26%, respectively. The comparison of different precipitants during the neutralization precipitation process showed that MgO was the best precipitant for the efficient removal of aluminum and low loss of rare earth. The results of removing aluminum revealed that when the final pH of the rare earth leaching solution was controlled to be 4.7, the reaction temperature was 25 °C, the slurry concentration of MgO was 0.3 mol/L, and the feeding rate of the MgO slurry was 0.5 mL/min, the removal rate of aluminum was 99.49%, and the loss rate of rare earth was 13.93%. The obtained purified rare earth solution contained 19 g/L of rare earth and less than 0.01 g/L of aluminum. Kinetic studies showed that the apparent activation energy of the aluminum removal process was 6.8 kJ/mol, indicating that the precipitation process was controlled by a mass transfer diffusion reaction. Full article

(This article belongs to the Section Mineral Processing and Extractive Metallurgy)

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Figure 1
<p>XRD pattern of the rare earth enrichment.</p> Full article ">Figure 2
<p>SEM–EDS spectrum of the rare earth enrichment.</p> Full article ">Figure 3
<p>Influence of H<sub>2</sub>SO<sub>4</sub> concentration on the leaching efficiencies of REEs, Al, Si, and Mg.</p> Full article ">Figure 4
<p>Effect of the liquid–solid ratio on the leaching efficiencies of REEs, Al, Si, and Mg.</p> Full article ">Figure 5
<p>Effect of temperature on the leaching efficiencies of REEs, Al, Si, and Mg.</p> Full article ">Figure 6
<p>Effect of time on the leaching efficiencies of REEs, Al, Si, and Mg.</p> Full article ">Figure 7
<p>XRD pattern of the leaching residue.</p> Full article ">Figure 8
<p>SEM–EDS spectrum of the leaching residue.</p> Full article ">Figure 9
<p>Species distribution in Al<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub>-RE<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub>-H<sub>2</sub>O system (<b>a</b>) La; (<b>b</b>) Y; (<b>c</b>) Nd; (<b>d</b>) Al.</p> Full article ">Figure 10
<p>(<b>a</b>) Influence of the precipitants on the aluminum removal rate; (<b>b</b>) Influence of the precipitants on the rare earth loss rate.</p> Full article ">Figure 11
<p>XRD pattern of the precipitated aluminum residue.</p> Full article ">Figure 12
<p>SEM picture of the precipitated aluminum residue (<b>a</b>) the aggregation of particles; (<b>b</b>) the single particle.</p> Full article ">Figure 13
<p>Effects of reaction temperatures on the aluminum removal rate and rare earth loss rate.</p> Full article ">Figure 14
<p>Effect of the MgO slurry concentration on the aluminum removal rate and rare earth loss rate.</p> Full article ">Figure 15
<p>Effect of MgO slurry feeding rate on the aluminum removal rate and rare earth loss rate.</p> Full article ">Figure 16
<p>Changes in the precipitation rate of aluminum at different temperatures with time.</p> Full article ">Figure 17
<p>Arrhenius plots at different temperatures.</p> Full article ">

23 pages, 7514 KiB

Open AccessArticle

Origin and Implication of the Paoma Granite in the Western Yangtze Block, South China Craton

by Awei Mabi, Changhong Zhong, Yanlong Li, Niuben Yu, Bo Liu, Feifei Lv, Gang Li and Ping Gan

Minerals 2025, 15(2), 188; https://doi.org/10.3390/min15020188 - 18 Feb 2025

The Meso- to Neoproterozoic magmatic rocks cropping out in the western Yangtze Block are pivotal to comprehending the tectonic-magmatic revolutionary processes of the South China Craton during the breakup and assembly of Rodinia. A combined study including a detailed geological survey, systemic measurement [...] Read more.

The Meso- to Neoproterozoic magmatic rocks cropping out in the western Yangtze Block are pivotal to comprehending the tectonic-magmatic revolutionary processes of the South China Craton during the breakup and assembly of Rodinia. A combined study including a detailed geological survey, systemic measurement of the geological section, petrographic observations, geochronology, and elemental geochemistry was carried out on the southern margin of the Paoma granitic pluton in SW China. The obtained data of major elements, along with the mineralogy that includes aluminosilicate minerals, indicate that the studied 825.7 ± 6.0 Ma Paoma granites are peraluminous, which is consistent with an affinity with S-type granites. They show seagull-shaped chondrite-normalized REE patterns with strongly negative Eu anomalies. They are enriched in LRREs and Large Ion Lithophile Elements but are depleted in High Field Strength Elements, with strongly negative Nb, Sr, P, and Ti anomalies. We conclude that the Paoma granite magma originated from the partial melting of clay-rich mudstone from the upper crust. The geochemical data of Paoma granite, integrated with the regional geological context, are consistent with a tectonic setting involving a fossil ridge subduction. The 825.7 Ma Paoma granite, along with the 830 Ma Guandaoshan gabbros showing N-MORB geochemical signatures, defines an east-west trending Neoproterozoic “slab window” in the WYB. Full article

(This article belongs to the Special Issue Petrology, Geochemistry and Geophysics of S-Type Granites and Migmatite Rocks)

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<p>(<b>a</b>) A brief geological map of the South China Craton showing the location of the studied Paoma granite [<a href="#B29-minerals-15-00188" class="html-bibr">29</a>]. (<b>b</b>) A simplified geological map for the WYB [<a href="#B27-minerals-15-00188" class="html-bibr">27</a>]. (<b>c</b>) The geological map of the south part of the Paoma granitic pluton showing the sample locations.</p> Full article ">Figure 2
<p>The representative optical field photographs of Paoma granite. (<b>a</b>) Specimen of the fine-grained biotite monzogranite; (<b>b</b>) the plagioclase megacrysts; (<b>c</b>,<b>d</b>) the weathering face and fresh rock of Paoma granite, where an enclave is highlighted by the red line; (<b>e</b>) the fine-grained biotite monzogranite in out-crop scale; and (<b>f</b>) the fine-grained biotite monzogranite unconformably overlain by layered Quaternary strata comprising coarse sand, boulders, and pebbly cobbles.</p> Full article ">Figure 3
<p>(<b>a</b>) U-Pb concordia plot and (<b>b</b>) weighted mean ages of representative zircons from the Paoma granite.</p> Full article ">Figure 4
<p>(<b>a</b>) A/CNK—A/NK plot [<a href="#B48-minerals-15-00188" class="html-bibr">48</a>]; (<b>b</b>) SiO<sub>2</sub> vs. (Na2O + K2O) diagram for classification of plutonites; (<b>c</b>) SiO<sub>2</sub> vs. FeOt/(FeOt + MgO) plot [<a href="#B47-minerals-15-00188" class="html-bibr">47</a>]; and (<b>d</b>) SiO<sub>2</sub> vs. MALI diagram [<a href="#B47-minerals-15-00188" class="html-bibr">47</a>].</p> Full article ">Figure 5
<p>(<b>a</b>) Chondrite-normalized REE patterns [<a href="#B50-minerals-15-00188" class="html-bibr">50</a>] and (<b>b</b>) primitive mantle-normalized multi-element spider diagram [<a href="#B51-minerals-15-00188" class="html-bibr">51</a>].</p> Full article ">Figure 6
<p>(<b>a</b>) Na<sub>2</sub>O versus K<sub>2</sub>O diagram [<a href="#B52-minerals-15-00188" class="html-bibr">52</a>] and (<b>b</b>) ACF graph distinguishing S-type granite from I-type granite [<a href="#B53-minerals-15-00188" class="html-bibr">53</a>,<a href="#B54-minerals-15-00188" class="html-bibr">54</a>].</p> Full article ">Figure 7
<p>Rb vs. Sr (<b>a</b>), Ba vs. Rb (<b>b</b>) [<a href="#B58-minerals-15-00188" class="html-bibr">58</a>], and the multiple plots of SiO<sub>2</sub> against Ba, Rb, and Sr (<b>c</b>–<b>e</b>) in the rocks of the Paoma granites.</p> Full article ">Figure 8
<p>(<b>a</b>) (Nb/Ta)—(Zr/Hf) variation graph of Paoma granites [<a href="#B57-minerals-15-00188" class="html-bibr">57</a>] and (<b>b</b>) (CaO/Na<sub>2</sub>O) versus (Rb/Sr) graph [<a href="#B60-minerals-15-00188" class="html-bibr">60</a>].</p> Full article ">Figure 9
<p>(<b>a</b>) Ternary diagram Al<sub>2</sub>O<sub>3</sub>/(FeO<sup>t</sup> + MgO); 3*CaO; 5*(K<sub>2</sub>O/Na<sub>2</sub>O) [<a href="#B69-minerals-15-00188" class="html-bibr">69</a>] and (<b>b</b>) binary plot of Al<sub>2</sub>O<sub>3</sub> + FeO<sup>t</sup> + MgO + TiO<sub>2</sub> vs. Al<sub>2</sub>O<sub>3</sub>/(FeO<sup>t</sup> + MgO + TiO<sub>2</sub>) [<a href="#B70-minerals-15-00188" class="html-bibr">70</a>].</p> Full article ">Figure 10
<p>(<b>a</b>) (Cao/Al<sub>2</sub>O<sub>3</sub>) vs. (CaO + Al<sub>2</sub>O<sub>3</sub>) diagram and (<b>b</b>) the zircon saturation temperature plot against Zr concentrations based on the whole-rock analysis to distinguish between ridge-subduction-related granites and post-collision-related granites (after [<a href="#B77-minerals-15-00188" class="html-bibr">77</a>]).</p> Full article ">Figure 11
<p>A “slab window” driven by ridge subduction formed in the WYB ~830 Ma. For the petrogenesis and tectonic background of Guandaoshan gabbros, please read Mabi et al., 2024 [<a href="#B26-minerals-15-00188" class="html-bibr">26</a>].</p> Full article ">

16 pages, 8572 KiB

Open AccessArticle

Effect of Flotation Variables on Slurry Rheological Properties and Flotation Performance of Lead–Zinc Sulfide Ores

by Kehua Luo, Chuanyao Sun and Tichang Sun

Minerals 2025, 15(2), 187; https://doi.org/10.3390/min15020187 - 17 Feb 2025

A slurry’s rheological properties significantly affect flotation performance. Flotation variables—including mineral composition, slurry concentration, and ore particle size—influence these properties by altering the interaction forces between mineral particles and the slurry’s microstructure, thereby impacting flotation outcomes. This study investigated the effects of flotation [...] Read more.

A slurry’s rheological properties significantly affect flotation performance. Flotation variables—including mineral composition, slurry concentration, and ore particle size—influence these properties by altering the interaction forces between mineral particles and the slurry’s microstructure, thereby impacting flotation outcomes. This study investigated the effects of flotation variables on the rheological properties and flotation performance of lead–zinc sulfide ores in two ternary systems comprising galena or sphalerite + kaolinite and quartz. Cryo-scanning electron microscopy and atomic force microscopy were used to analyze the slurries’ interaction forces and microstructure. The results show that finer ore particle sizes increase the formation of particle agglomerates, leading to larger structures and higher slurry apparent viscosity. This improves the metal mineral recovery rate during flotation but simultaneously increases gangue mineral entrainment, reducing concentrate grade. As the slurry concentration increases, the ternary system with kaolinite as the main gangue mineral forms a denser and more rigid honeycomb network structure. This results in higher yield stress and apparent viscosity, which negatively impacts lead and zinc sulfide separation during flotation. In contrast, the quartz-dominated system forms a slightly denser, stacked structure that lacks a solid network and thus maintains lower yield stress and apparent viscosity, which favors mineral separation. Adding sodium hexametaphosphate enhances particle dispersion by increasing repulsive forces between mineral particles. This thins or disrupts the kaolinite network structure, reducing the slurry’s apparent viscosity and yield stress, thereby improving its rheological properties and facilitating the flotation separation of lead and zinc sulfide minerals. Full article

(This article belongs to the Section Mineral Processing and Extractive Metallurgy)

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<p>XRD patterns of the (<b>a</b>) galena, (<b>b</b>) sphalerite, (<b>c</b>) quartz, and (<b>d</b>) kaolinite mineral samples used in this study.</p> Full article ">Figure 2
<p>Relationship between yield stress (<b>a</b>), apparent viscosity (<b>b</b>), and ore particle size in slurry.</p> Full article ">Figure 3
<p>Flotation indices of the two slurries as a function of ore particle size.</p> Full article ">Figure 4
<p>Aggregate particle size of mineral particles in the two systems.</p> Full article ">Figure 5
<p>Yield stress (<b>a</b>) and apparent viscosity (<b>b</b>) as a function of slurry concentration for the two systems.</p> Full article ">Figure 6
<p>Flotation indices of the two systems as a function of slurry concentration.</p> Full article ">Figure 7
<p>Slurry microstructure at a concentration of 30 wt% (<b>a</b>: galena system, <b>b</b>: sphalerite system).</p> Full article ">Figure 8
<p>Slurry microstructure at a concentration of 50 wt% (<b>a</b>: galena system, <b>b</b>: sphalerite system).</p> Full article ">Figure 9
<p>Yield stress (<b>a</b>) and apparent viscosity (<b>b</b>) as a function of mineral fraction for the two slurries.</p> Full article ">Figure 10
<p>Flotation indices of the two systems as a function of mineral fraction.</p> Full article ">Figure 11
<p>Slurry microstructure when the main gangue mineral is kaolinite (metal minerals:quartz:kaolinite = 1:1:8; <b>a</b>: galena system, <b>b</b>: sphalerite system).</p> Full article ">Figure 12
<p>Slurry microstructure when the main gangue mineral is quartz (metal minerals:quartz:kaolinite = 1:8:1; <b>a</b>: galena system, <b>b</b>: sphalerite t system).</p> Full article ">Figure 13
<p>Relationship between yield stress (<b>a</b>), apparent viscosity (<b>b</b>), and sodium hexametaphosphate dosage for the two slurries.</p> Full article ">Figure 14
<p>Flotation indices of the two systems as a function of sodium hexametaphosphate dosage.</p> Full article ">Figure 15
<p>Slurry structure without sodium hexametaphosphate (<b>a</b>: galena system, <b>b</b>: sphalerite system).</p> Full article ">Figure 16
<p>Slurry structure with sodium hexametaphosphate (<b>a</b>: galena system, <b>b</b>: sphalerite system).</p> Full article ">Figure 17
<p>Effect of sodium hexametaphosphate on interaction forces between metal and gangue mineral particles.</p> Full article ">Figure 18
<p>Relationship between yield stress (<b>a</b>), apparent viscosity (<b>b</b>), and slurry strength.</p> Full article ">Figure 19
<p>Relationship between flotation indices and slurry conditioning intensity.</p> Full article ">Figure 20
<p>Effect of approach velocity on interaction forces between metallic and gangue mineral particles.</p> Full article ">

13 pages, 33523 KiB

Open AccessArticle

Mapping Sulphide Mineralization in the Hawiah Area Using Transient Electromagnetic Methods

by Panagiotis Kirmizakis, Abid Khogali, Konstantinos Chavanidis, Timothy Eatwell, Tomos Bryan and Pantelis Soupios

Minerals 2025, 15(2), 186; https://doi.org/10.3390/min15020186 - 17 Feb 2025

The Arabian–Nubian Shield (ANS) hosts numerous volcanogenic massive sulphide (VMS) deposits formed in submarine volcanic settings and enriched by hydrothermal processes, making it a critical region for mineral exploration due to the types of deposits it hosts and its geological complexity. The Wadi [...] Read more.

The Arabian–Nubian Shield (ANS) hosts numerous volcanogenic massive sulphide (VMS) deposits formed in submarine volcanic settings and enriched by hydrothermal processes, making it a critical region for mineral exploration due to the types of deposits it hosts and its geological complexity. The Wadi Bidah Mineral Belt (WBMB), located within the Arabian Shield, contains over 30 polymetallic VMS occurrences associated with an island arc system active between 950 and 800 million years ago. Despite its mineral potential, the WBMB still needs to be explored, with limited geophysical studies to support resource evaluation. This study focuses on the Hawiah area, a prominent VMS site within the WBMB, to delineate subsurface mineralization using transient electromagnetic (TEM) methods. TEM surveys were conducted to characterize the conductivity structure and identify potential zones of sulphide mineralization. Data were processed and inverted to generate 1D, 2D, and 3D resistivity models, providing critical insights into the depth, geometry, and continuity of the mineralized zones based on the final 3D resistivity distribution. The results revealed distinct conductive (very low resistivity) anomalies, correlating with known surface gossans and inferred sulphide-rich layers, and extended these features into the subsurface. The integration of TEM results with geological and geochemical data highlights the effectiveness of this approach in detecting and mapping concealed mineral deposits in complex geological environments. This study advances the understanding of VMS systems in the WBMB and demonstrates the potential of TEM surveys as a key tool for mineral exploration in the Arabian Shield. Full article

(This article belongs to the Special Issue Novel Methods and Applications for Mineral Exploration, Volume III)

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<p>(<b>a</b>) The location of the Hawiah VMS deposit within the Arabian Peninsula, (<b>b</b>) geological map of WBMB depicting the location of Hawiah VMS deposits (modified from Beziat and Donzeau [<a href="#B20-minerals-15-00186" class="html-bibr">20</a>]), and (<b>c</b>) the study area, including key features such as the Crossroads Lode, Central Area, and Camp Lode.</p> Full article ">Figure 2
<p>Generalized cross-section of the main oxidation state zones (oxide, transitional, and fresh) in the Hawiah VMS deposit, based on Eatwell [<a href="#B21-minerals-15-00186" class="html-bibr">21</a>] and Ashley [<a href="#B22-minerals-15-00186" class="html-bibr">22</a>].</p> Full article ">Figure 3
<p>(<b>a</b>) Extended area of interest around the Hawiah deposit, (<b>b</b>) survey area with TEM stations marked by green squares, and (<b>c</b>) acquisition setup for each TEM station showing the arrangements of the transmitter (100 × 100 m) and receiver (10 × 10 m) loops for data collection.</p> Full article ">Figure 4
<p>Geological cross-section shows the lithological unit distribution and mineralization within the Hawiah VMS deposit. The TEM profile (red line) highlights resistivity variations associated with the mineralized zones.</p> Full article ">Figure 5
<p>Resistivity depth slices from the TEM survey show variations within depth intervals ranging from 0-300 m. Each panel (<b>a</b>–<b>f</b>) represents a specific depth interval, highlighting the resistivity’s lateral and vertical distribution. The color scale reflects resistivity values in ohm-meters (Ohm.m), where lower values (blue color) indicate conductive zones and higher values (red/orange colors) represent resistive zones.</p> Full article ">Figure 6
<p>Petrographic images of core samples showing various lithological and mineralogical features under plane-polarized transmitted light. All fields of view are 0.5 to 2 mm across.</p> Full article ">

27 pages, 26571 KiB

Open AccessArticle

Sources and Enrichment Mechanisms of Rare-Earth Elements in the Mosuoying Granites, Sichuan Province, Southwest China

by Xuepeng Xiao, Guoxin Li, Shuyi Dong, Lijun Qian and Lihua Ou

Minerals 2025, 15(2), 185; https://doi.org/10.3390/min15020185 - 17 Feb 2025

Ion-adsorption-type rare-earth element (iREE) deposits, a primary source of global heavy REE (HREE) ores, have attracted wide attention worldwide due to their concentrated distributions and irreplaceable role in the field of cutting-edge technologies. In recent years, iREE mineralization has been reported in the [...] Read more.

Ion-adsorption-type rare-earth element (iREE) deposits, a primary source of global heavy REE (HREE) ores, have attracted wide attention worldwide due to their concentrated distributions and irreplaceable role in the field of cutting-edge technologies. In recent years, iREE mineralization has been reported in the overlying weathering crust of the Mosuoying granites within the Dechang counties, Sichuan Province, Southwest China, suggesting great potential for the formation of iREE deposits. The Mosuoying granites, acting as the primary carrier of REE pre-enrichment, govern the contents and distribution patterns of REEs in their weathering crust. Therefore, investigating the sources and enrichment mechanisms of REEs in the parent rocks will provide a critical theoretical basis for the scientific exploitation and utilization of iREE deposits. In this study, we investigated the migration and enrichment of REEs in the Mosuoying granites (850–832 Ma) using petrography, geochronology, geochemical, and Sr-Nd-Hf isotopic data. The results reveal that the REE enrichment in the Mosuoying granites might be associated with both the melting of crustal felsic rocks and the magmatic-hydrothermal evolution. On the one hand, the granites exhibit different REE patterns. Compared to the light REE (LREE)-rich granites, the HREE-rich granites feature higher SiO₂ contents, higher differentiation index (DI), lower Nb/Ta and Zr/Hf ratios, and more significant negative Eu anomalies, indicating that the crystal fractionation of magmas governed the differentiation of REEs. Furthermore, the hydrothermal fluids further promoted the formation of the HREE-rich granites. On the other hand, the geochemical characteristics suggest that they are A-type granites. Regarding the isotopic characteristics, the Mosuoying granites exhibit negative whole-rock εNd(t) and zircon εHf(t) values, suggesting an evolved crustal source. Therefore, we suggest that the high REE contents in the Mosuoying A-type granites might originate from the partial melting of felsic rocks in a shallow crustal source under high-temperature and low-pressure conditions. Specifically, the high-temperature A-type granitic magmas caused the partial melting of the felsic crustal materials to release REEs; concurrently, these magmas enhanced the solubility of REEs in melt during magmatic evolution, inhibiting the separation of REE-bearing minerals from the melts. These increased the REE contents of the granites. The high-temperature heat source might be associated with the process where the asthenospheric mantle experienced upwelling along slab windows and heated continental crust in the Neoproterozoic extensional setting. Full article

(This article belongs to the Section Mineral Deposits)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Geological maps showing the distribution of the Mosuoying granites. (<b>a</b>) Modified after [<a href="#B27-minerals-15-00185" class="html-bibr">27</a>] and the location of the study area in the Yangtze Block, South China, and (<b>b</b>) modified after [<a href="#B23-minerals-15-00185" class="html-bibr">23</a>].</p> Full article ">Figure 2
<p>Simplified geological map of Mosuoying granites in the Dechang area, Southwest China.</p> Full article ">Figure 3
<p>Hand specimen and representative microscope photographs of the Mosuoying granites. (<b>a</b>) KY-05 granite sample (<b>b</b>,<b>e</b>) rock-forming minerals in the Mosuoying granites (<b>c</b>) plagioclases manifest sericitization and are metasomatized by calcite and muscovite (<b>d</b>) KY-08 granite sample (<b>f</b>) biotite is filled between other minerals, showing partial chlorite alteration. Pl—plagioclase; Kfs—K-feldspar; Qtz—quartz; Bt—biotite; Ms—muscovite; Ser—Sericite; Chl—chlorite; Zrn—zircon; Cal—calcite.</p> Full article ">Figure 4
<p>BSE images of REE-bearing minerals in samples from the Mosuoying granites. (<b>a</b>) monazite is altered to allanite, (<b>b</b>) titanite is associated with apatite, zircon, and bastnasite, (<b>c</b>) thorite is paragenetic with zircon, apatite, and bastnasite as mineral aggregates, (<b>d</b>) secondary allanite sparsely contains monazite, (<b>e</b>) thorite is closely associated with magnetite in K-feldspar, (<b>f</b>) fergusonite occurs as idiomorphic independent minerals within mica minerals, (<b>g</b>) thorite and bastnasite are related to the metasomatism of zircon by hydrothermal fluids, (<b>h</b>) Y- and Th-rich silicate mineral is paragenetic with zircon, siderite, and K-feldspar, (<b>i</b>) yttrocrasite occurs near kaolinite formed by the weathering of K-feldspar, (<b>j</b>) yttrocrasite and allanite are filled in the fissures of mica minerals, (<b>k</b>) yttrocrasite displays significant zonal textures, (<b>l</b>) yttrocrasite is paragenetic with rutile and ilmenite. Mineral abbreviations: Mnz—monazite, Aln—allanite, Ab—Albite, Ttn—titanite, Bas—bastnasite. Zrn—zircon, Ap—apatite, Thr—thorite, Mt—Magnetite, Bt—biotite, Kfs—K-feldspar, Grt—garnet, Fer—fergusonite, Opx-(Y)—orthorhombic pyroxene-(Y), Sd—siderite, Qtz—quartz, Ytt—yttrocrasite, Kln—kaolinite, Rt—rutile, Ilm—ilmenite.</p> Full article ">Figure 5
<p>Representative cathodoluminescence (CL) images of zircon grains for the LREE-rich granite (<b>a</b>) and HREE-rich granite (<b>b</b>) in the study area.</p> Full article ">Figure 6
<p>LA-ICP-MS U-Pb zircon concordia diagrams for the LREE-rich granite (<b>a</b>,<b>b</b>) and HREE-rich granite (<b>c</b>,<b>d</b>) in the study area.</p> Full article ">Figure 7
<p>(<b>a</b>) (Na<sub>2</sub>O + K<sub>2</sub>O) vs. SiO<sub>2</sub> diagram [<a href="#B39-minerals-15-00185" class="html-bibr">39</a>]. Ir = Irvine boundary line; (<b>b</b>) K<sub>2</sub>O vs. SiO<sub>2</sub> diagram [<a href="#B40-minerals-15-00185" class="html-bibr">40</a>]; (<b>c</b>) A/NK vs. A/CNK diagram [<a href="#B41-minerals-15-00185" class="html-bibr">41</a>]. A—Al<sub>2</sub>O<sub>3</sub>, C—CaO, N—Na<sub>2</sub>O, K—K<sub>2</sub>O; (<b>d</b>) SiO<sub>2</sub> vs. A.R diagram [<a href="#B42-minerals-15-00185" class="html-bibr">42</a>]. A.R (alkalinity ratio) = (Al<sub>2</sub>O<sub>3</sub> + CaO + Na<sub>2</sub>O + K<sub>2</sub>O)/(Al<sub>2</sub>O<sub>3</sub> − CaO − Na<sub>2</sub>O − K<sub>2</sub>O). The data for granites from the literature are from 790 Ma Yonglang and 840 Ma Kuanyu granites [<a href="#B22-minerals-15-00185" class="html-bibr">22</a>,<a href="#B24-minerals-15-00185" class="html-bibr">24</a>,<a href="#B27-minerals-15-00185" class="html-bibr">27</a>].</p> Full article ">Figure 8
<p>Harker variation diagrams for major-element oxides of samples from the Mosuoying granites. (SiO<sub>2</sub> vs. Al<sub>2</sub>O<sub>3</sub> (<b>a</b>), TiO<sub>2</sub> (<b>b</b>), Fe<sub>2</sub>O<sub>3</sub> (<b>c</b>), P<sub>2</sub>O<sub>5</sub> (<b>d</b>), MgO (<b>e</b>), CaO (<b>f</b>)). The data sources are identical to <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 9
<p>(<b>a</b>) Chondrite-normalized REE patterns and (<b>b</b>) primitive mantle-normalized trace element spidergram of samples from the Mosuoying granites. Normalized values of the primitive mantle and chondrite are from [<a href="#B43-minerals-15-00185" class="html-bibr">43</a>]. The data sources are identical to <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 10
<p>(<b>a</b>) (<sup>87</sup>Sr/<sup>86</sup>Sr)<sub>i</sub> vs. εNd(t) diagram (modified after [<a href="#B10-minerals-15-00185" class="html-bibr">10</a>,<a href="#B24-minerals-15-00185" class="html-bibr">24</a>]. (<b>b</b>) Zircon U-Pb age vs. εNd(t) diagram. (<b>c</b>) Zircon U-Pb age vs. εHf(t) diagram and (<b>d</b>) histograms showing the εHf(t) isotope ratios and Hf model ages of the Mosuoying granites from the western margin of the Yangtze Block, Southwest China. The data sources are identical to <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 11
<p>(<b>a</b>) Nb/Ta vs. Zr/Hf diagram and (<b>b</b>) CaO/(Na<sub>2</sub>O + K<sub>2</sub>O) vs. Rb/Sr diagram (modified after [<a href="#B56-minerals-15-00185" class="html-bibr">56</a>]). Mesozoic ore-bearing granites in the Nanling Mountains referring to [<a href="#B47-minerals-15-00185" class="html-bibr">47</a>]. The data sources are identical to <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 12
<p>(<b>a</b>) (Na<sub>2</sub>O + K<sub>2</sub>O)/CaO vs. Zr + Nb + Ce + Y, (<b>b</b>) FeO<sup>T</sup>/MgO vs. Zr + Nb + Ce + Y, (<b>c</b>) Nb vs. 10,000 × Ga/Al and (<b>d</b>) Zr vs. 10,000 × Ga/Al diagram [<a href="#B64-minerals-15-00185" class="html-bibr">64</a>], (<b>e</b>) Zr saturation temperature (T<sub>Zr</sub>) vs. SiO<sub>2</sub>, (<b>f</b>) Al<sub>2</sub>O<sub>3</sub>/(MgO + TiO<sub>2</sub> + Fe<sub>2</sub>O<sub>3</sub><sup>T</sup>) vs. Al<sub>2</sub>O<sub>3</sub> + MgO + TiO<sub>2</sub> + Fe<sub>2</sub>O<sub>3</sub><sup>T</sup> diagram [<a href="#B68-minerals-15-00185" class="html-bibr">68</a>]. T<sub>Zr</sub> (°C) = 12900/(ln D<sup>zircon/melt</sup> + 0.85 M + 2.95)—273.5, D<sup>zircon/melt</sup> = 496000/Zr contents in the melts (ppm), M = molar ratio of (Na + K + 2Ca)/(Al × Si) [<a href="#B67-minerals-15-00185" class="html-bibr">67</a>]. The data sources are identical to <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 13
<p>(<b>a</b>) Nb vs. Y and (<b>b</b>) Rb vs. Y+Nb diagrams (modified after [<a href="#B93-minerals-15-00185" class="html-bibr">93</a>]). (<b>c</b>) Nb-Y-Ce and (<b>d</b>) Nb-Y-Zr/4 discrimination diagrams [<a href="#B89-minerals-15-00185" class="html-bibr">89</a>] for the Mosuoying granites from the western margin of the Yangtze Block, South China. WPG: within-plate granites, syn-COLG: syn-collisional granites, ORG: ocean ridge granites, VAG: volcanic arc granites. The data sources are the same as <a href="#minerals-15-00185-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 14
<p>Conceptual model for the generation of Neoproterozoic REE-rich Mosuoying granite in the Dechang area. (<b>a</b>) the partial melting of felsic rocks in a shallow crustal source provides REEs for the melts, (<b>b</b>) magmatic-hydrothermal evolution promotes the formation of REE-rich granites. <a href="#minerals-15-00185-f014" class="html-fig">Figure 14</a>b modified after [<a href="#B96-minerals-15-00185" class="html-bibr">96</a>].</p> Full article ">

17 pages, 10844 KiB

Open AccessArticle

Mineral Prospectivity Mapping in Xiahe-Hezuo Area Based on Wasserstein Generative Adversarial Network with Gradient Penalty

by Jiansheng Gong, Yunhe Li, Miao Xie, Yunhui Kong, Rui Tang, Cheng Li, Yixiao Wu and Zehua Wu

Minerals 2025, 15(2), 184; https://doi.org/10.3390/min15020184 - 16 Feb 2025

The Xiahe-Hezuo area in Gansu Province, China, located in the West Qinling Metallogenic Belt, is characterized by complex regional geological structures and abundant mineral resources. A number of gold-polymetallic deposits have been identified in this region, demonstrating significant potential for gold-polymetallic mineral prospecting [...] Read more.

The Xiahe-Hezuo area in Gansu Province, China, located in the West Qinling Metallogenic Belt, is characterized by complex regional geological structures and abundant mineral resources. A number of gold-polymetallic deposits have been identified in this region, demonstrating significant potential for gold-polymetallic mineral prospecting within the metallogenic belt. This study focuses on regional Mineral Prospectivity Mapping (MPM) in the Xiahe-Hezuo area. To address the common challenge of small-sample data limitations in geological prediction, we introduce a Wasserstein Generative Adversarial Network with gradient penalty (WGAN-GP) to generate high-fidelity geological feature samples, effectively expanding the training dataset. A Convolutional Neural Network (CNN) was used to train and predict on both pre- and post-augmentation data. The experimental results show that, before augmentation, the CNN model’s Receiver Operating Characteristic (ROC) value was 0.9648. After data augmentation with the WGAN-GP, the CNN model’s ROC value improved to 0.9792. Additionally, the CNN model’s classification performance was significantly enhanced, with the training set accuracy increasing by 5% and the test set accuracy improving by 2%, successfully overcoming the issue of insufficient model generalization caused by small sample sizes. The mineralization prediction results based on data augmentation delineate five prospective mineralization targets, whose spatial distribution exhibits strong correlations with known deposits and fault structural belts, confirming the reliability of the predictions. This study validates the effectiveness of data augmentation techniques in MPM and provides a transferable technical framework for MPM in data-scarce regions. Full article

(This article belongs to the Special Issue Application of Big Data Mining, Machine Learning and Artificial Intelligence in Geoscience, 2nd Edition)

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17 pages, 8008 KiB

Open AccessArticle

An Exploratory Study of Quartz Grain Surface Microtextures in Dam-Break Flood Deposits from the Middle Reaches of the Yarlung Tsangbo River

by Zhihang Lu, Mengying He, Jinying Xu, Xilin Cao, Jingran Zhang, Zhigang Zhang, Xinggong Kong and Zhijun Zhao

Minerals 2025, 15(2), 183; https://doi.org/10.3390/min15020183 - 16 Feb 2025

This study focused on the surface microtextures of quartz grains deposited by dam-break floods in Jiacha Gorge, situated in the middle reaches of the Yarlung Tsangpo River. Utilizing a scanning electron microscope (SEM), 200 quartz grains were observed and analyzed based on their [...] Read more.

This study focused on the surface microtextures of quartz grains deposited by dam-break floods in Jiacha Gorge, situated in the middle reaches of the Yarlung Tsangpo River. Utilizing a scanning electron microscope (SEM), 200 quartz grains were observed and analyzed based on their microtextural features. Our findings reveal specific microtextures—such as angular outlines, high relief, flat cleavage surfaces, conchoidal fractures, and steps—that serve as clear indicators of the extreme energy associated with dam-break floods in Jiacha Gorge, distinguishing them from meteorological floods and smaller-scale dam-break events. These features also facilitate the differentiation of dam-break flood deposits from those of other sedimentary environments. This research demonstrates that quartz microtextures are a valuable tool for reconstructing sediment transport processes during extreme flood events. We recommend integrating microtextural analysis with complementary methods to refine interpretations and address methodological uncertainties in future studies. Full article

(This article belongs to the Section Crystallography and Physical Chemistry of Minerals & Nanominerals)

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<p>(<b>A</b>) Locations of the Yarlung Tsangpo River drainage and other flood deposit sites compared to this study [<a href="#B31-minerals-15-00183" class="html-bibr">31</a>,<a href="#B32-minerals-15-00183" class="html-bibr">32</a>]; (<b>B</b>) topographic map of the Yarlung Tsangpo River drainage and the major paleo-dammed lakes and gorges in the middle reaches; (<b>C</b>) tectonic background of the Yarlung Tsangpo River. YZS: Yarlung Tsangpo suture; STD: South Tibetan detachment; MCT: main central thrust; MBT: main boundary thrust.</p> Full article ">Figure 2
<p>(<b>A</b>) Topographic map of dam-break flood deposit profiles in this study and existing studies [<a href="#B26-minerals-15-00183" class="html-bibr">26</a>,<a href="#B40-minerals-15-00183" class="html-bibr">40</a>,<a href="#B41-minerals-15-00183" class="html-bibr">41</a>,<a href="#B71-minerals-15-00183" class="html-bibr">71</a>] within the Jiacha Gorge section in the Yarlung Tsangpo River; (<b>a</b>–<b>g</b>) the lithological column for each profile; (<b>B</b>–<b>F</b>) representative photos of the sampling profiles.</p> Full article ">Figure 3
<p>Frequency of quartz surface microtextures. High-frequency features are marked in red font, while moderately common features are marked in light red font.</p> Full article ">Figure 4
<p>Typical microtextures in Jiacha Gorge sample. (<b>A</b>) High relief and angular outline. (<b>B</b>) Low relief and angular outline. (<b>C</b>) Low relief and subangular outline. (<b>D</b>) Medium relief and angular outline. (<b>E</b>) Medium relief and angular outline. (<b>F</b>) High relief and angular outline. (<b>G</b>) Medium relief and angular outline. (<b>H</b>) Medium relief and subrounded outline. (<b>I</b>) Frequent occurrence of conchoidal fractures near a flat cleavage surface. (<b>J</b>) V-shaped percussion marks on a flat cleavage surface. (<b>K</b>) Frequent occurrence of both arcuate and straight steps. (<b>L</b>) Conchoidal fractures coexist with steps. (<b>M</b>) A mechanical curved crack and clearly visible upturned plates. (<b>N</b>) Large V-shaped percussion marks on a pre-weathered surface. The left part is a newly formed fresh surface. (<b>O</b>) A straight groove on a fresh surface. (<b>P</b>) A fresh surface covered with grooves and V-shaped percussion marks. (<b>Q</b>) Frequent occurrence of solution pits. Notice that solution pits overlap fresh surfaces, indicating these chemical features formed later than mechanical features. (<b>R</b>) Silica precipitation on flat cleavage surface. (<b>S</b>) Oriented etch pits in a depression on the grain, indicating a diagenesis process. (<b>T</b>) The grain surface is covered with silica precipitation. Some curved cracks can be seen, which are more likely to have originated from chemical processes. Abbreviations: SS—straight step; AS—arcuate step; VPM—V-shaped percussion mark; CC—curved crack; FCS—flat cleavage surface; SG—straight groove; CG—curved groove; UP—upturned plate; SCF—small conchoidal fracture; MCF—medium conchoidal fracture; LCF—large conchoidal fracture; SOP—solution pit; SIP—silica pellicle; OEP—oriented etch pit.</p> Full article ">Figure 5
<p>The mean values and coefficients of variation for quartz surface microtextures from the Jiacha Gorge.</p> Full article ">Figure 6
<p>Typical inherited microtextures. (<b>A</b>) The upper part of the grain has undergone extensive chemical alteration, while other parts remain fresh surfaces. This clearly indicates that these chemical microtextures are inherited. (<b>B</b>) The left side of the grain has a fresh surface with straight steps, while the rest has undergone extensive chemical rework. (<b>C</b>) The lower part of the grain is a newly formed fresh surface, while the flat cleavage surface on the upper part has been weathered and has numerous marks on it. (<b>D</b>) Details of the flat cleavage surface on grain G show numerous V-shaped percussion marks and impact grooves. (<b>E</b>) Abrasion fatigue and chatter marks on the flat cleavage surface, with chatter marks indicating glacial modification. (<b>F</b>) Parallel striations indicate glacial work. (<b>G</b>) A bulbous edge showing a very rounded outline. The rest of the grain is angular and has fresh surfaces resulting from grain fragmentation. (<b>H</b>) Details of bulbous edges on grain A. Abbreviations: BE—bulbous edge; CPM—crescentic percussion mark; SOP—solution pit; AS—arcuate step; AF—abrasion fatigue; PS—parallel striation; OEP—oriented etch pit; FCS—flat cleavage surface; SG—straight groove.</p> Full article ">Figure 7
<p>Contrast between dam-break flood deposits and those from other sedimentary environments. Data for other sedimentary environments are sourced from Vos et al. [<a href="#B46-minerals-15-00183" class="html-bibr">46</a>].</p> Full article ">

22 pages, 5770 KiB

Open AccessArticle

The Influence of Conical Pick Cutter Wear Conditions on Physical Characteristics and Particle Size Distribution of Coal: Health and Safety Considerations with a Focus on Silica

by Manso Sesay, Jamal Rostami, Syd Slouka, Hugh Miller, Rennie Kaunda and Anshuman Mohanty

Minerals 2025, 15(2), 182; https://doi.org/10.3390/min15020182 - 16 Feb 2025

This study investigates the correlations between the wear conditions of conical pick cutters and key variables such as the physical properties (shape, aspect ratio, roughness), explosive potential, health and safety implications, and particle size distribution of coal dust and larger fragments using the [...] Read more.

This study investigates the correlations between the wear conditions of conical pick cutters and key variables such as the physical properties (shape, aspect ratio, roughness), explosive potential, health and safety implications, and particle size distribution of coal dust and larger fragments using the linear cutting machine (LCM). This research was conducted within the framework of recent regulatory developments, notably implementing the new silica rule in the mining and construction sectors and climate change consideration. This study reveals critical insights into optimizing operational processes while adhering to stringent health and safety regulations. The findings indicate that as cutting tools wear, there is a significant increase in generated fine particles, including respirable crystalline silica (RCS), which elevates the risk of respiratory diseases and, in the case of coal dust, a higher potential for explosions. The results show that the silica content in respirable dust is a function of rock mineralogy; however, the results showed that the absolute amount of silica-containing dust increased with bit wear in rocks containing pertinent minerals. For the larger fragments, the new bit produced a 1699 fragment count, while the completely worn-out bit produced a 5608 count. The results of the dust concentration show that the new bit produces 89.2 mg/m³ (17.84%); the moderate bit produces 165.1 mg/m³ (33.03%), and the worn-out bit produces 245.6 mg/m³ (49.13%). Moreover, this study highlights the impact of bit wear on the production of larger fragments, which decreases with tool degradation, further contributing to dust generation. These results suggest the necessity for proactive equipment maintenance, enhanced dust control measures, and continuous monitoring of cutting tool wear to ensure compliance with regulatory standards and to protect workers’ health and safety. Full article

(This article belongs to the Special Issue Size Distribution, Chemical Composition and Morphology of Mine Dust)

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<p>A linear cutting machine used to cut the rock samples in stable conditions, with the sled on which the rock box sits, the cylinders that move the rocks horizontally, the saddle that holds the pick cutter, and the LVDT to measure the force.</p> Full article ">Figure 2
<p>Conical pick cutters used to cut all the rock samples. The pick on the far left is the new pick; the one in the middle is the moderately worn-out pick, and the last one on the right is the completely worn-out pick.</p> Full article ">Figure 3
<p>Dust collection apparatus: (<b>a</b>) The cassettes with filters used to collect the respirable dust; (<b>b</b>) The rock sample placed on the rock box under the saddle where the pick cutter is connected and cuts the rock horizontally.</p> Full article ">Figure 4
<p>Fines collection point: (<b>a</b>) Two L-square rulers are placed at the point where the fractured rock that remains on the surface of the rock is collected manually for Wipfrag particle size distribution analysis; (<b>b</b>) Fines collection vacuum and paper filter used to collect the fines that remained on the surface for laser diffraction for particle size distribution analysis.</p> Full article ">Figure 5
<p>Dust image and mineralogy: (<b>a</b>) The image of the dust obtained under the FE-SEM; (<b>b</b>) Mineralogy obtained from the EDS/EDAX (FE-SEM) of the coal dust sample that is used as a baseline to ensure each sample looked at is primarily coal with a cutoff point 0.25 µm in diameter.</p> Full article ">Figure 6
<p>FE-SEM image and Clemex 49 PE image: (<b>a</b>) The raw image of dust obtained from the FE-SEM; (<b>b</b>) Clemex 49 PE analysis of raw FE-SEM images for physical properties evaluation of dust particles.</p> Full article ">Figure 7
<p>Workflow chart, which gives the work breakdown structure of the entire research process from rock preparation to result analysis.</p> Full article ">Figure 8
<p>Aerodynamic diameters of dust particles and percent channel for all pick wear conditions.</p> Full article ">Figure 9
<p>Physical properties of dust and wear conditions of CSV data obtained from the Clemex 49 analysis.</p> Full article ">Figure 10
<p>These figures show the physical diameter and particle size distribution of fines obtained from the laser diffraction as raw data of representative samples: (<b>a</b>) a new bit; (<b>b</b>) moderately worn-out bit; (<b>c</b>) completely worn-out bit.</p> Full article ">Figure 11
<p>Physical properties of fines and wear conditions: (<b>a</b>) Physical properties of fines of new bit; (<b>b</b>) Physical properties of fines of moderate bit; (<b>c</b>) Physical properties of fines of worn-out bit.</p> Full article ">Figure 12
<p>Picture of rock fragments from the LCM testing in Coal samples spread out for capturing an image to analyze its particle size distribution using the Wipfrag software, Version 4.</p> Full article ">

17 pages, 2360 KiB

Open AccessArticle

Chemical and Bioreductive Leaching of Laterites and Serpentinite Waste with Possible Reuse of Solid Residues for CO₂ Adsorption

by Agnieszka Pawlowska, Zygmunt Sadowski and Katarzyna Winiarska

Minerals 2025, 15(2), 181; https://doi.org/10.3390/min15020181 - 15 Feb 2025

Experiments were conducted to evaluate domestic low-grade laterites and serpentinite waste as potential secondary sources of nickel and magnesium and to assess leaching residues for carbon dioxide adsorption. Solids were leached chemically using sulfuric acid, while bioreductive dissolution under anoxic conditions employed a [...] Read more.

Experiments were conducted to evaluate domestic low-grade laterites and serpentinite waste as potential secondary sources of nickel and magnesium and to assess leaching residues for carbon dioxide adsorption. Solids were leached chemically using sulfuric acid, while bioreductive dissolution under anoxic conditions employed a consortium of microorganisms dominated by Sulfobacillus. The efficiency of laterite bioreduction was 26.81% for Ni and 63.92% for Mg. In the case of serpentinite, 20.54% Ni and 92.88% Mg were extracted. The chemical dissolution yielded 26.73% Ni and 61.37% Mg in the case of laterites and 16.20% Ni and 77.49% Mg for serpentinite waste. Specific surface area was analyzed during the processes, showing a systematic increase over time. Based on the changes in this parameter, a mathematical description of the process was proposed using a shrinking particle model (SPM). Except for laterite bioreduction, leaching was shown to be a two-stage process controlled by a chemical reaction. The serpentinite solid processed in the presence of microorganisms exhibited the highest surface area (267 m²/g) and a CO₂ adsorption capacity of 19.9 cm³/g. Full article

(This article belongs to the Special Issue Sustainable Extraction and Reuse of Metallurgical Wastes: Towards Circular Practices)

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<p>XRD diagram of laterite ore.</p> Full article ">Figure 2
<p>XRD diagram of serpentinite.</p> Full article ">Figure 3
<p>Changes of (<b>a</b>) magnesium and (<b>b</b>) nickel concentration during chemical leaching.</p> Full article ">Figure 4
<p>Magnesium (<b>a</b>) and nickel (<b>b</b>) dissolution during bioreductive leaching.</p> Full article ">Figure 5
<p>Laterite (<b>a</b>) before process, (<b>b</b>) after chemical leaching, (<b>c</b>) and bioleached residue, and serpentinite (<b>d</b>) before process, (<b>e</b>) after chemical leaching, (<b>f</b>) and after bioprocess.</p> Full article ">Figure 6
<p>The surface area changes during (<b>a</b>) chemical and (<b>b</b>) bioreductive dissolution.</p> Full article ">Figure 7
<p>Plots and correlation coefficients for various controlling mechanisms of chemical leaching.</p> Full article ">Figure 8
<p>Plots and correlation coefficients for various controlling mechanisms of laterite bioreduction (<b>a</b>) film diffusion, (<b>b</b>) chemical reaction control.</p> Full article ">Figure 9
<p>Plots and correlation coefficients for various controlling mechanisms of serpentinite bioreduction (<b>a</b>) stage I, (<b>b</b>) stage II.</p> Full article ">Figure 10
<p>CO<sub>2</sub> adsorption isotherms of carbon dioxide onto laterite and serpentinite waste. “-0”, solid before leaching; “-ch”, after chemical; and “-bio”, bioreductive leaching.</p> Full article ">

17 pages, 2741 KiB

Open AccessArticle

Leucophosphite and Associated Minerals in the Fossil Bat Guano Deposit in Gaura cu Muscă Cave, Locvei Mountains, Romania

by Delia-Georgeta Dumitraş and Ştefan Marincea

Minerals 2025, 15(2), 180; https://doi.org/10.3390/min15020180 - 15 Feb 2025

This paper presents a new account of the mineralogy of the bat guano deposit in Gaura cu Muscă Cave, Locvei Mountains, Romania. The cave, which, in its main proportion, is a wet, “live” cave, has a dry portion hosting guano. Biogenic leucophosphite is [...] Read more.

This paper presents a new account of the mineralogy of the bat guano deposit in Gaura cu Muscă Cave, Locvei Mountains, Romania. The cave, which, in its main proportion, is a wet, “live” cave, has a dry portion hosting guano. Biogenic leucophosphite is one of the main compounds of the fossil bat guano association in the cave, where it occurs together with hydroxylapatite, taranakite, ardealite, calcite, quartz and illite (the 2M1 polytype). The mineral species from the cave were characterized by optical methods, scanning electron microscopy, wet-chemical analysis, X-ray powder diffraction, Fourier-transform infrared and inductively coupled plasma – atomic emission spectrometry. The crystal-chemical formula of leucophosphite from Gaura cu Muscă is [K_0.978Na_0.003(NH₄)_0.014](Al_0.085Fe_1.903Mg_0.001Mn_0.006)(PO₄)₂(OH)_0.973·2H₂O. The cell parameters calculated for the same sample are a = 9.813(6) Å, b = 9.749(6) Å, c = 9.631(9) Å and β = 102.30(2)°. The infrared spectrum affords the presence of (PO₄)³⁻, (HPO₄)²⁻, (NH₄)⁺ and (OH)⁻ ions, together with H₂O molecules. The band multiplicity on the IR absorption spectrum suggests that the phosphate groups in the structure have C_s punctual symmetry. The host deposit was formed under extremely “dry” conditions that favored a sharp decrease in the pH of solutions derived from the guano mass. Full article

(This article belongs to the Special Issue Microbial Biomineralization and Organimineralization)

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Figure 1
<p>A sketch of Gaura cu Muscă Cave (<b>middle</b>—redrawn from [<a href="#B8-minerals-15-00180" class="html-bibr">8</a>]) showing the location of the cave on the Romanian map (<b>top</b>). Bottom: detail of the sampling points, which are marked with red stars.</p> Full article ">Figure 2
<p>SEM photomicrographs of typical aggregates of phosphates in the guano deposit in Gaura cu Muscă Cave. (<b>A</b>) Aggregate of leucophosphite crystals. The arrow indicates a better-shaped crystal. (<b>B</b>) Aggregate of randomly oriented crystals of leucophosphite. Flattened but broken pseudohexagonal shapes can be observed. (<b>C</b>) Aggregate of taranakite crystals. The left arrow indicates a well-shaped hexagonal tabular crystal, whereas the right arrow indicates a radial cluster of crystals. (<b>D</b>) Group of randomly oriented crystals of taranakite. The hexagonal forms can be distinguished as are marked by an arrow. (<b>E</b>) Aggregate of stacked hydroxylapatite crystals. The hexagonal contour of a crystal can be observed. (<b>F</b>) Detail of a deposit of hydroxylapatite crystals on a carbonate boulder. (<b>G</b>) Assemblage of randomly oriented crystals of ardealite with visible spearhead terminations. (<b>H</b>) Aggregate of randomly oriented platy crystals of ardealite. The arrow indicates a well-shaped crystal.</p> Full article ">Figure 2 Cont.
<p>SEM photomicrographs of typical aggregates of phosphates in the guano deposit in Gaura cu Muscă Cave. (<b>A</b>) Aggregate of leucophosphite crystals. The arrow indicates a better-shaped crystal. (<b>B</b>) Aggregate of randomly oriented crystals of leucophosphite. Flattened but broken pseudohexagonal shapes can be observed. (<b>C</b>) Aggregate of taranakite crystals. The left arrow indicates a well-shaped hexagonal tabular crystal, whereas the right arrow indicates a radial cluster of crystals. (<b>D</b>) Group of randomly oriented crystals of taranakite. The hexagonal forms can be distinguished as are marked by an arrow. (<b>E</b>) Aggregate of stacked hydroxylapatite crystals. The hexagonal contour of a crystal can be observed. (<b>F</b>) Detail of a deposit of hydroxylapatite crystals on a carbonate boulder. (<b>G</b>) Assemblage of randomly oriented crystals of ardealite with visible spearhead terminations. (<b>H</b>) Aggregate of randomly oriented platy crystals of ardealite. The arrow indicates a well-shaped crystal.</p> Full article ">Figure 3
<p>FT-IR spectrum recorded for a selected sample of leucophosphite from Gaura cu Muscă Cave (Sample PGM 1 B).</p> Full article ">Figure 4
<p>FT-IR spectrum of selected sample of hydroxylapatite from Gaura cu Muscă Cave.</p> Full article ">

14 pages, 2534 KiB

Open AccessArticle

Effect of Different Crushing Methods on Chalcopyrite Liberation and Heavy Media Preconcentration

by Jian Xu, Hailiang Wang, Chunqing Gao, Lin Zhang, Hanxu Yang, Mingyu Sai, Jun Hu, Qiuju Huang and Hongzhen Luo

Minerals 2025, 15(2), 179; https://doi.org/10.3390/min15020179 - 14 Feb 2025

In order to find a short, economically feasible process for chalcopyrite preconcentration and to provide a reference for the preconcentration of similar copper sulfide ores, the particle size characteristics of the crushed products from a high-pressure grinding roller (HPGR) and jaw crusher (JC) [...] Read more.

In order to find a short, economically feasible process for chalcopyrite preconcentration and to provide a reference for the preconcentration of similar copper sulfide ores, the particle size characteristics of the crushed products from a high-pressure grinding roller (HPGR) and jaw crusher (JC) were analyzed, as well as the liberation degree and fracture characteristics of the chalcopyrite. The float–sink test (FST) was carried out on the crushed products, and the effects of the two crushing methods on the FSTs of the crushed products were compared. The research results show that at the same crushing fineness, the chalcopyrite liberation in HPGR products can be enhanced by 14%~18% compared with the JC. The single-particle crushing of the JC tends to produce intergranular fracturing of chalcopyrite, while the lamination crushing of the HPGR produces more transgranular fracturing of chalcopyrite; the chalcopyrite in the −5 + 0.5 mm size fraction mainly produces intergranular fracturing, and the chalcopyrite in the −0.5 mm size fraction mainly produces transgranular fracturing. The FST results show that heavy media preconcentration was suitable for chalcopyrite, and, in the optimal conditions of a size fraction of −3 + 0.5 mm and separation density of 2.55 g/cm³, the grade and distribution rate of Cu in the sinks obtained by HPGR-FST were 0.35% and 89.86%, respectively, and the floats yield was 24.76%, with a better enrichment of sinks and higher floats yields, which was better when compared with that of the JC-FST. Full article

(This article belongs to the Special Issue Recent Advances in Ore Comminution)

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25 pages, 26870 KiB

Open AccessArticle

Astronomical Forcing of the Siliciclastic-Carbonate Mixed Sedimentation in the Late Pennsylvanian of the Tarim Basin, West China

by Rui Han, Shangfeng Zhang, Shunshe Luo, Yaning Wang, Gaoyang Gong, Jianhao Liang, Chengcheng Zhang, Cai Cheng and Liang Zhang

Minerals 2025, 15(2), 178; https://doi.org/10.3390/min15020178 - 14 Feb 2025

The Azigan Formation and the Lower Member of the Tahaqi Formation, dating to the Late Pennsylvanian, are pivotal exploration targets within the Tarim Basin. This region exhibits extensive siliciclastic-carbonate mixed sediments. However, the lack of high-resolution sequence stratigraphic frameworks significantly limits advanced petroleum [...] Read more.

The Azigan Formation and the Lower Member of the Tahaqi Formation, dating to the Late Pennsylvanian, are pivotal exploration targets within the Tarim Basin. This region exhibits extensive siliciclastic-carbonate mixed sediments. However, the lack of high-resolution sequence stratigraphic frameworks significantly limits advanced petroleum geological research. Using principles of sequence stratigraphy and cyclostratigraphy and leveraging outcrop and thin section data alongside GR series analysis, this study systematically investigates the lithological, cyclic, and sequence stratigraphic characteristics of these formations. A total of 12 different lithofacies were identified, and 3 third-order sequences, 15 fourth-order sequences, and 16 long eccentricity cycles were delineated. A 1.2 Ma long slope signal was also identified. An astronomical timescale was established with 298.9 Ma as the anchor, defining the boundary between the upper and lower members of the Tahaqi Formation, revealing a link between long eccentricity cycles and the formation of fourth-order sequences. Moreover, the relationship between the 1.2 Ma long obliquity cycle and third-order sequences, as well as its role in driving sea-level changes in southwestern Tarim, is explored. The interplay between long obliquity and eccentricity cycles influenced the region’s mixed siliceous clastic and carbonate deposition. Warm and humid climatic conditions coupled with sea-level rise enhanced the input and transport of clastic materials, facilitating large-scale mixed sedimentation. Full article

(This article belongs to the Section Mineral Exploration Methods and Applications)

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<p>Location map of the study area. (<b>a</b>) Paleogeographic map of the Tarim Basin at 300 Ma (adapted from Christopher R., 2021) [<a href="#B24-minerals-15-00178" class="html-bibr">24</a>]; (<b>b</b>) Tectonic subdivision of the Tarim Basin; (<b>c</b>) Composite stratigraphic column illustrating Carboniferous lithology and tectonic movements in the southwestern subregion.</p> Full article ">Figure 2
<p>Lithological characteristics of coastal facies (<b>a</b>) parallel bedding and low-angle cross-bedding in sandstone, geological hammer—yellow circle (30 cm); (<b>b</b>) parallel bedding in sandstone; (<b>c</b>) low-angle cross-bedding in calcareous sandstone; (<b>d</b>) trough cross-bedding in sandstone; (<b>e</b>) in feldspar-bearing quartz sandstone, particles exhibit line contact, medium sorting, and sub-rounded to sub-angular, rounded grains, observed under cross-polarized light (CPL),the black particles are identified as quartz and exhibit the characteristic of complete extinction; (<b>f</b>) calcareous sandstone with calcite cement between the grains, occasional bioclastic fragments observed (indicated by the yellow arrow).</p> Full article ">Figure 3
<p>Lithological characteristics of the peritidal facies (<b>a</b>) microcrystalline dolomite (CPL); (<b>b</b>) medium-thick, layered dolomite and gray, medium-layered mudstone-dolomitic limestone, with distinct scaly texture observable on the F12 dolomite, geological hammer—yellow circle (30 cm); (<b>c</b>) gray, medium- to thin-bedded nodular limestone; (<b>d</b>) dark gray, thin-bedded algal wackestone; (<b>e</b>) algal wackestone with a micritic matrix; (<b>f</b>) bioclastic packstone.</p> Full article ">Figure 4
<p>Lithological characteristics of the grain beach facies (<b>a</b>) Gray, thick-bedded oolitic limestone with terrigenous quartz clasts, geological hammer—yellow circle (30 cm); (<b>b</b>) Terrigenous quartz clastic bioclastic oolitic limestone and bioclastic granular limestone; (<b>c</b>) Bioclastic grainstone with sand-sized clasts, primarily consisting of sand grains, Fusulina (indicated by the white arrow), and foraminifera, along with other bioclastic fragments; (<b>d</b>) Land-derived clastic sand-sized grainstone, with sand grains (indicated by the white arrow) and siliceous clasts (indicated by the yellow arrow) scattered between particles; (<b>e</b>) Oolitic packstone; (<b>f</b>) Land-derived clastic oolitic limestone, terrigenous quartz clasts (indicated by the yellow arrow), and echinoderm fragments (indicated by the white arrow).</p> Full article ">Figure 5
<p>Sequence stratigraphy analysis of the lower section of the Azigan Formation and Tahaqi Formation (<b>a</b>,<b>e</b>) Gamma ray curves from the Aitegou and Qipan profiles; (<b>b</b>,<b>f</b>) Lithological column diagrams of the Aitegou and Qipan profiles; (<b>c</b>,<b>g</b>) Wavelet transform analysis of the Aitegou and Qipan profiles, with the red line representing the detailed signal curve, and the wavelet coefficient scale set to 512 (a = 512); (<b>d</b>,<b>h</b>) INPEFA curves from the Aitegou and Qipan profiles; (<b>i</b>) Abbreviations: SB—Sequence boundary, MFS—Maximum flooding surface, TST—Transgressive systems tract, HST—Highstand systems tract.</p> Full article ">Figure 6
<p>Comparison of sedimentary facies and sequence stratigraphy profiles of the lower section of the Azigan-Tahaqi Formation in the southwest Tarim Basin.</p> Full article ">Figure 7
<p>Results of cycle stratigraphy analysis in the depth domain (<b>a</b>) GR sequence of the Aitegou profile; (<b>b</b>) Lithological column diagram of the Aitegou profile; (<b>c</b>) Gaussian bandpass filtering at ~17 m (red, with a passband of 0.057 ± 0.011 cycles/m) and ~5.7 m (green, with a passband of 0.678 ± 0.004 cycles/m) for the Aitegou profile; (<b>d</b>,<b>e</b>) 2π MTM power spectrum (top) and eFFT frequency spectrum (bottom) for the Aitegou profile; (<b>f</b>) GR sequence of the Qipan profile; (<b>g</b>) Lithological column diagram of the Qipan profile; (<b>h</b>) Gaussian bandpass filtering at ~17 m (red, with a passband of 0.067 ± 0.023 cycles/m) and ~5.7 m (green, with a passband of 0.65 ± 0.005 cycles/m) for the Qipan profile; (<b>i</b>,<b>j</b>) 2π MTM power spectrum (top) and eFFT frequency spectrum (bottom) for the Qipan profile.</p> Full article ">Figure 8
<p>Results of COCO and eCOCO analysis of the detrended GR sequences, with sedimentation rates in the range of 1–8 cm/kyr, step size of 0.1 cm/kyr, and 5000 Monte Carlo simulations; (<b>a</b>) COCO analysis results for the Aitegou profile (upper) and detrended SGR eCOCO diagram (lower); (<b>b</b>) Null hypothesis (upper) and evolutionary null hypothesis (H<sub>0</sub>) significance level (lower) for the Aitegou profile; (<b>c</b>) Astronomical orbital matching number (upper) and evolutionary astronomical orbital matching number (lower) for the Aitegou profile; (<b>d</b>) COCO analysis (upper) and eCOCO diagram (lower) for the detrended GR sequence of the Qipan profile; (<b>e</b>) Null hypothesis (upper) and H<sub>0</sub> significance level (lower) for the Qipan profile; the black line represents the sedimentation rate curve calculated based on the long eccentricity cycle (405 kyr) for both profiles; (<b>f</b>) Astronomical orbital matching number (upper) and evolutionary astronomical orbital matching number (lower) for the Qipan profile.</p> Full article ">Figure 9
<p>Results of the time-domain cyclic stratigraphy analysis: (<b>a</b>) 2 πMTM power spectrum of the 405 kyr-tuned gamma sequence for the Aitegou profile; (<b>b</b>) 2 πMTM power spectrum of the 405 kyr-tuned gamma sequence for the Qipan profile; (<b>c</b>) WT scale diagram of the 405 kyr-tuned gamma sequence for the Aitegou profile; (<b>d</b>) WT scale diagram of the 405 kyr-tuned gamma sequence for the Qipan profile.</p> Full article ">Figure 10
<p>The slope periods and DYNOT’s A.M. for the Aitegou and Qipan profiles: (<b>a</b>,<b>c</b>) The slope A.M. of the tuned gamma ray curves for the Aitegou and Qipan profiles; (<b>b</b>,<b>d</b>) The slope A.M. of the DYNOT curves for the Aitegou and Qipan profiles.</p> Full article ">Figure 11
<p>Comparison of sequence stratigraphy and cyclic stratigraphy: (<b>a</b>) detrended gamma sequence of the Aitegou profile; (<b>b</b>) long eccentricity cycle of the Aitegou profile; (<b>c</b>) INPEFA sequence of the Aitegou profile; (<b>d</b>) fourth-order sequence of the Aitegou profile; (<b>e</b>) detrended gamma sequence of the Qipan profile; (<b>f</b>) long eccentricity cycle of the Qipan profile; (<b>g</b>) INPEFA sequence of the Qipan profile; (<b>h</b>) fourth-order sequence of the Qipan profile.</p> Full article ">Figure 12
<p>Aitegou profile sedimentary noise sea level change model: (<b>a</b>) Global sea level change curve [<a href="#B69-minerals-15-00178" class="html-bibr">69</a>]; (<b>b</b>) global CO<sub>2</sub> change curve [<a href="#B70-minerals-15-00178" class="html-bibr">70</a>]; (<b>c</b>) global δ<sup>13</sup>C change curve [<a href="#B70-minerals-15-00178" class="html-bibr">70</a>]; (<b>d</b>) Aitegou profile detrended gamma curve with 405 kyr filtering (red line), bandwidth (0.0025 ± 0.0001 cycles/kyr); (<b>e</b>) 36.2 kyr filtering, bandwidth (0.0283 ± 0.0023 cycles/kyr); (<b>f</b>) 1.2 Ma slope A.M. filtering, bandwidth (0.00078 ± 0.00012 cycles/kyr); (<b>g</b>) DYNOT and ρ1 of the tuned gamma sequence, window 300–500 kyr, confidence interval derived from 2000 iterations of Monte Carlo analysis; (<b>h</b>) DYNOT median curve with ~1.2 Ma filtering, bandwidth (0.00084 ± 0.00015 cycles/kyr).</p> Full article ">Figure 13
<p>Mixed sedimentary model influenced by astronomical orbital forcing.</p> Full article ">

27 pages, 8263 KiB

Open AccessArticle

Geochemical Characteristics and Paleoenvironmental Significance of No. 5 Coal in Shanxi Formation, Central–Eastern Ordos Basin (China)

by Bo Pan, Kangle Wang, Guodong Dong, Xingze Zhou, Yuhang Chen, Yipeng Zhuang, Xing Gao and Xiaowei Du

Minerals 2025, 15(2), 177; https://doi.org/10.3390/min15020177 - 14 Feb 2025

Coal is a carrier of geological information, preserving paleoenvironmental and paleoclimatic data from geological history. The Ordos Basin hosts abundant coal resources with significant potential for exploration and development. The geochemical properties of coal and their associated geological information offer key insights into [...] Read more.

Coal is a carrier of geological information, preserving paleoenvironmental and paleoclimatic data from geological history. The Ordos Basin hosts abundant coal resources with significant potential for exploration and development. The geochemical properties of coal and their associated geological information offer key insights into coal formation, coal–rock gas generation, and the identification of favorable development areas. This study focuses on the No. 5 coal of the Shanxi Formation in the central and eastern Ordos Basin. Building on previous research and advancements, this study reveals the geochemical attributes and sedimentary background of coal through core observations, drilling data, macerals, and element analyses. The results indicate that the No. 5 coal primarily consists of bright and semi-bright coal, characterized by medium ash yield and high fixed carbon. The macerals of the coal are predominantly vitrinite (64.08% on average), followed by inertinite (24.92% on average) and liptinite (2.8% on average). The source material for the No. 5 coal in the Shanxi Formation is primarily derived from felsic igneous rocks. The varying distribution patterns of rare earth elements suggest differences in the sources of coal materials. From the Late Carboniferous to the Early Permian, the North China Craton was located in tropical paleolatitudes in the Northern Hemisphere. The warm and humid paleoclimate facilitated the deposition of coal. Fluctuations in local lake levels and sedimentary system evolution resulted in an oxidized and oxygen-deficient water. The No. 5 coal is characterized by a relatively small TPI value and a relatively large GI value, indicating a coal-forming environment with deep water coverage, poor water circulation, or relative stagnation. This resulted in slow peat accumulation, allowing plant remains to fully gelatinize. The findings enhance the understanding of the geochemical characteristics of the No. 5 coal and the factors controlling its development within the Shanxi Formation of the central and eastern Ordos Basin. These results provide a theoretical basis for coal exploration and development. Full article

(This article belongs to the Section Mineral Geochemistry and Geochronology)

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Figure 1
<p>(<b>a</b>) The location of the Ordos Basin. (<b>b</b>) The tectonic feature of the Ordos Basin. (<b>c</b>) The typical lithology column of the Cisuralian in the Ordos basin. (<b>d</b>) West–east (<b>A</b>,<b>A’</b>) and south–north (<b>B</b>,<b>B’</b>) well-tie section.</p> Full article ">Figure 2
<p>(<b>a</b>) Mudstone, S120 well, 2647 m; (<b>b</b>) black bright coal, Y116 well, 2152 m; (<b>c</b>) black bright coal, Y116 well, 2153.4 m; (<b>d</b>) semi-bright coal, S120 well, 2469.5 m; (<b>e</b>) semi-dull coal, Y101 well, 2359.5 m; (<b>f</b>) mudstone with carbonized plant fossils, Y101 well, 2365.5 m.</p> Full article ">Figure 3
<p>Images in the samples under secondary electron. (<b>a</b>) Vitrinite and its surface film-like minerals (mainly calcite), H21 well, 2558.47 m; (<b>b</b>) EDX spectrum of calcite; (<b>c</b>) mixture of minerals (alcite, clay minerals), MT5 well, 2324.6 m; (<b>d</b>) fusinite filled with kaolinite and calcite, TZ1H well, 2298.88 m; (<b>e</b>) EDX spectrum of kaolinite; (<b>f</b>) kaolinite, J37 well, 3370.17 m; (<b>g</b>) rutile and kaolinite filling interlayer cracks, WT1H well, 3163.8 m; (<b>h</b>) EDX spectrum of rutile; (<b>i</b>) clay and organic components mixed, WT1H well, clay minerals, 3158.69 m.</p> Full article ">Figure 4
<p>(<b>a</b>) Telocollinite, Y116 well, 2152.99 m; (<b>b</b>) telocollinite and desmocollinite, WT1H, 3158.69 m; (<b>c</b>) fusinite, J26 well, 3032.58 m; (<b>d</b>) degradofusinite, Y116 well, 2152.99 m; (<b>e</b>) pyrofusinite, H21 well, (<b>f</b>) natural char, J26 well, 3032.58 m; (<b>g</b>) resinite, J26 well, 3031.7 m; (<b>h</b>) clay minerals, Y101 well, 2359.27 m; (<b>i</b>) pyrite, Y116 well, 2152.67 m.</p> Full article ">Figure 5
<p>Concentration coefficient of trace elements of coal samples from the Shanxi Formation in the eastern Ordos Basin.</p> Full article ">Figure 6
<p>Upper continental crust (UCC)-normalized REE patterns for coal seams from the Shanxi Formation in the eastern Ordos Basin [<a href="#B33-minerals-15-00177" class="html-bibr">33</a>].</p> Full article ">Figure 7
<p>Relationship diagrams for Al<sub>2</sub>O<sub>3</sub> vs. TiO<sub>2</sub> (<b>a</b>) and Nb/Y vs. Zr/TiO<sub>2</sub> × 10<sup>−4</sup> (<b>b</b>) for identifying the source rock [<a href="#B65-minerals-15-00177" class="html-bibr">65</a>].</p> Full article ">Figure 8
<p>(<b>a</b>) The intersection map of TPI and GI of coal seams [<a href="#B38-minerals-15-00177" class="html-bibr">38</a>]. (<b>b</b>) The intersection map of GWI and VI of coal seams [<a href="#B3-minerals-15-00177" class="html-bibr">3</a>].</p> Full article ">Figure 9
<p>(<b>a</b>) U/Th of coal seam samples; (<b>b</b>) Ni/Co of coal seam samples; (<b>c</b>) V/Cr of coal seam samples; (<b>d</b>) Cu/Zn of coal seam samples.</p> Full article ">Figure 10
<p>(<b>a</b>) V/Zr and (<b>b</b>) Zr/Cu of coal seam samples.</p> Full article ">Figure 11
<p>(<b>a</b>) An example of an Early Permian (290 Ma) global paleogeographic reconstruction (modified from Scotese [<a href="#B83-minerals-15-00177" class="html-bibr">83</a>]) showing a low- to mid-latitude position of the NCC. (<b>b</b>) CIA, (<b>c</b>) temperature, and (<b>d</b>) mean annual precipitation of coal samples.</p> Full article ">Figure 12
<p>Relationship model between inertinite content and oxygen content in atmosphere [<a href="#B11-minerals-15-00177" class="html-bibr">11</a>].</p> Full article ">Figure 13
<p>Variations in ash yield, vitrinite and geochemical indicators in the samples.</p> Full article ">Figure 14
<p>The coal accumulation model of the Shanxi Formation in the study area.</p> Full article ">

19 pages, 6991 KiB

Open AccessArticle

Two-Step Shear Flocculation for High-Efficiency Dewatering of Ultra-Fine Tailings

by Ying Yang, Xiaohui Liu, Liqiang Zhang and Miaomiao Guo

Minerals 2025, 15(2), 176; https://doi.org/10.3390/min15020176 - 14 Feb 2025

The high-efficiency dewatering of ultra-fine tailings is one of the most prominent challenges in tailings thickening. The two-step shear flocculation process represents a promising practical method to achieve the dewatering of ultra-fine tailings. In this paper, a small self-made experimental device was used [...] Read more.

The high-efficiency dewatering of ultra-fine tailings is one of the most prominent challenges in tailings thickening. The two-step shear flocculation process represents a promising practical method to achieve the dewatering of ultra-fine tailings. In this paper, a small self-made experimental device was used to simulate the two-step shear flocculation process of ultra-fine tailings, strengthening the effect of shear failure and shear coagulation, and we explored the mass fraction of ultra-fine tailings, floc structure size, floc strength, and regeneration performance of tailings slurry according to the variation in shear action in different stages. In addition, the synergistic mechanism of shear failure and shear coagulation in the two-step high-efficiency dewatering process of ultra-fine tailings was proposed. The results show that the dewatering of ultra-fine tailings was significantly improved by two-step flocculation, and the mass fraction of tailings can reach more than 71%. In the primary floc failure stage, the value of G₁T₁ should be higher than 100,000, and in the secondary floc regeneration stage, the value of G₂T₂ should be in the range of 7000~11,000. This paper provides a reference for the regulation of the shear mode and action range in the two-step flocculation process of ultra-fine tailings. Full article

(This article belongs to the Special Issue Advances in Mine Backfilling Technology and Materials)

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<p>Particle size distribution of tailings.</p> Full article ">Figure 2
<p>The two-step flocculation experimental device. (<b>a</b>) Photo of experimental device; (<b>b</b>) schematic diagram of experimental device.</p> Full article ">Figure 3
<p>Variation in the mass fraction of ultra-fine tailings with shear action (G<sub>1</sub>T<sub>1</sub>) in the primary floc failure stage.</p> Full article ">Figure 4
<p>Variation in the mass fraction of ultra-fine tailings with shear action (G<sub>2</sub>T<sub>2</sub>) in the secondary floc regeneration stage.</p> Full article ">Figure 5
<p>Variation in average particle size of broken flocs with shear failure (G<sub>1</sub>T<sub>1</sub>).</p> Full article ">Figure 6
<p>SEM of flocs under different shear failure values in the primary floc failure stage. (<b>a</b>) Low shear (G<sub>1</sub>T<sub>1</sub> = 30,000); (<b>b</b>) high shear (G<sub>1</sub>T<sub>1</sub> = 120,000).</p> Full article ">Figure 7
<p>Variation in average particle size of secondary flocs with shear coagulation (G<sub>2</sub>T<sub>2</sub>).</p> Full article ">Figure 8
<p>SEM of flocs under different shear coagulation levels in the secondary floc regeneration stage. (<b>a</b>) Low shear (G<sub>2</sub>T<sub>2</sub> = 3000); (<b>b</b>) high shear (G<sub>2</sub>T<sub>2</sub> = 9000).</p> Full article ">Figure 9
<p>Variation in floc strength factor with shear failure (G<sub>1</sub>T<sub>1</sub>).</p> Full article ">Figure 10
<p>Variation in floc regeneration factor with shear coagulation (G<sub>2</sub>T<sub>2</sub>).</p> Full article ">Figure 11
<p>Schematic diagram of the flocculation principle in the hypothesis regarding shear failure and shear coagulation’s synergism.</p> Full article ">

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Research on Ikaite—Natural Occurrences and Synthetic Mineral Precipitation Guest Editors: Gabrielle J. Stockmann, Juan Diego Rodríguez-Blanco
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Mineral Dissolution and Precipitation in Geologic Porous Media Guest Editors: Jianping Xu, Na Liu
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