Minerals

The Mianhuakeng deposit, located within the Zhuguangshan batholith in the Nanling area, is currently recognized as the largest granite-related uranium deposit in China. A portion of the uranium ore bodies is spatially associated with NE-trending mafic veins within the granite. In this study, the field investigation, zircon U-Pb dating, S and Pb isotope analysis, and whole-rock geochemical analysis were conducted on these mafic veins to explore their crystallization age, petrogenesis, tectonic setting, and relationships with uranium mineralization. The weighted mean result of zircon U-Pb is 189 ± 3 Ma, suggesting that the mafic dyke was crystallized during the Early Jurassic. The whole-rock geochemistry and isotopes exhibit characteristics of intraplate basalts, suggesting that the mafic dykes originate from an enriched mantle source consisting of garnet–spinel lherzolite, with an estimated partial melting of 1%–5%. Mafic magmas underwent low-degree contamination from the lower crust during upwelling, induced by the extension of the lithosphere during the Early Jurassic. The analyses of pyrite sulfur isotopes in mafic samples vary between −2.9‰ and 1.8‰, significantly different from that of pyrite (−14.4‰ to −7.8‰) formed during the uranium mineralization. Furthermore, the ages of the pitchblende of 127–54 Ma are much younger than the crystallization ages of mafic dykes, indicating that the mafic magmas did not contribute to the uranium mineralization of Mianhuakeng deposit during magmatism. However, the abundant reducing minerals (e.g., pyrite, hornblende, and Fe²⁺-bearing minerals) in the mafic dykes can act as a redox barrier, reducing mobile U⁶⁺ to immobile U⁴⁺ during fluid–rock interaction, thereby facilitating uranium precipitation from the hydrothermal ore-forming fluids. The secondary fractures created by the intrusion of mafic magma probably provided favorable pathways for the movement of hydrothermal fluids.

The foundation of successful mineral exploration is precise bauxite horizon demarcation and grade estimation. Although core analysis is the industry standard method, it is costly, labor-intensive, and has a relatively low processing capacity. To overcome these limitations, this study constructed an Extreme Gradient Boosting (XGBoost) classifier based on the logging parameters of natural gamma logging (GR), natural gamma spectroscopy logging (GGL), three-lateral logging (LL3), and compensated density logging (CDN) in order to achieve the automation of ore layer identification and grade prediction. The karst-type bauxite in Lvliang, Shanxi, was used to validate the research. The model was trained using the data from four wells in Shenjiazhuang. The trained model was directly applied to a blind well in Xingxian without parameter adjustment. Strong cross-site generalization was demonstrated by horizon recognition, which achieved 98.18% accuracy, 96.62% precision, 91.49% recall, and an F1 score of 93.99%. Based on the Al/Si ratio (A/S) and the content of Al₂O₃, the grade prediction classifies the samples into three grades: high-, medium-, and low-grade. The Mean Absolute Errors (MAEs) for the prediction of high- and medium-grade subsets of Al₂O₃ were 0.906 and 1.643, respectively, and those for A/S were 1.224 and 1.146, respectively. And the coefficient of determination (R²) for each grade level was greater than 0.8. These results support XGBoost’s field applicability and resilience for intelligent bauxite exploration.

Ceramic balls, as an emerging grinding medium, require a systematic method for optimizing their size distribution in wet ball mills. This study proposes an innovative approach that integrates Duan’s semi-theoretical ball diameter formula with breakage statistical mechanics to determine the optimal ceramic ball size distribution. The ideal ball diameters for grinding 2.36–3.0 mm, 1.18–2.36 mm, 0.60–1.18 mm, and 0.30–0.60 mm tungsten ore were identified as 55 mm, 50 mm, 35 mm, and 20 mm, respectively. Subsequently, the optimal ball size distribution was formulated as CB3: Ø55 mm:Ø50 mm:Ø35 mm:Ø20 mm = 30%:40%:20%:10%. Comparative sieve analysis and discrete element method (DEM) simulations confirmed that the CB3 distribution yields the highest proportion of qualified particles, the most favorable collision frequency, and the greatest kinetic energy among all tested configurations. The proposed method demonstrates both accuracy and practicality, providing a theoretical foundation for the industrial application of ceramic ball grinding systems.