Pyrite is widely distributed in the Earth’s crust and oceanic systems, and it generally occurs as pentagonal dodecahedra, cubic, octahedral, idiomorphic crystals, or dense, massive, granular, and nodular aggregates. In this study, representative pyrite samples from Hunan, Fujian, Jiangxi, Anhui in China and from Peru were collected. By utilizing a range of analytical techniques, including petrography, X-ray diffraction, infrared spectrum, Raman spectrum, major and trace element analysis, as well as sulfur stable isotope analysis, we comprehensively depict the mineralogical and spectroscopic characteristics of pyrite, and the evolution processes of the physical and chemical conditions of mineralization can be qualitatively constrained. The spectroscopic results indicate all samples show a relatively narrow absorption band with weak to moderate intensity in the vicinity of 343 cm⁻¹, which represents the bending vibration of the Fe-[S₂]²⁻ molecular bond. The Co content of pyrite exhibits the characteristics of a positive correlation with temperature and a negative correlation with oxygen fugacity, respectively. The δ³⁴S isotopic compositions of colloidal pyrite are in the range of 0.03 to 0.67, which are close to meteoric sulfur and mantle sulfur compositions, while the δ³⁴S values of nodular pyrite fall within the range of granite, indicating the characteristics of mixtures of sulfur sources are mainly related to magmatic activity. Our results provide insight into the formation mechanisms of pyrite in different environments, its mineralization, and the ore genesis of deposits. Moreover, the integrated analytical methods for pyrite are provided, which can define theoretical guidance for the exploration and development of mineral resources.

Featuring subtle lithological alterations in the host rocks and containing colossal gemstone crystals, the scheelite deposit at Xuebaoding in the Pingwu region of Sichuan Province exhibits characteristics typical of a vein-like hydrothermal-type deposit. The scheelite from the Xuebaoding region is renowned for its high saturation of color, perfect crystal shape, and pure color. In this study, its crystal structure and mineralogical, geochemical, and in situ Sr-Nd isotope characteristics are all systematically characterized. Our objective is to determine the source of ore-forming materials, the timing of the mineralization, and the chemical composition of scheelite, including major elements, trace elements, and rare earths elements (REE). The scheelite samples were analyzed with a variety of methods such as polarizing microscopy, X-ray powder diffraction (XRD), X-ray fluorescence spectrometry (XRF), electron probing, and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). In addition, conventional gemological tests were performed using instruments including gemstone microscopes, GI-UVB ultraviolet fluorescent lamps, grating spectroscopy, etc. The results demonstrate that scheelite exhibits a high refractive index, excellent crystallinity, and a granular structure. Clear color bands and ring structures are observed within the minerals, accompanied by interference colors of light blue, blue, and yellow. Additionally, the mineral components are relatively concentrated, with muscovite and illite serving as accessory minerals. Furthermore, the chemical composition of scheelite reveals a WO₃/CaO mass ratio that approaches or exceeds the ideal value. Moreover, it exhibits a wide range of variations in total rare earth element (∑REE) content, which is characterized by an enrichment of light rare earths (LREE), significant negative Eu anomalies, and insignificant Ce anomalies. In addition, the metallogenic formation of scheelite can be estimated to have occurred during the Toarcian stage in the Lower Jurassic Epoch period, approximately 183 Ma. The study further revealed that A-type granite serves as the genesis type of scheelite, with most of the ore-forming materials originating from the upper crust and a few derived from younger crustal sources.

Pyrite occurs in a wide range of ore-forming environments, and its trace element and rare earth element (REE) compositions are important geochemical indicators for determining its genetic origin, thereby providing valuable constraints for ore deposit research and mineral exploration. Machine learning, as a data-driven technique, offers new insights into the genesis types of pyrite by comprehensively analyzing data and uncovering underlying patterns. In this study, representative pyrite samples with diverse morphologies, including both sedimentary and hydrothermal types, were collected. Based on electron probe microanalysis (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), a comprehensive analysis of pyrite genesis was conducted. Furthermore, an artificial neural network (ANN) machine learning algorithm was employed to establish a classification model, and the predictive performance of this trained model was compared against that of traditional discrimination methods. The results show that when only trace elements were used as input features, the training set yielded a classification accuracy of 64.3% for sedimentary pyrite and 93.9% for hydrothermal pyrite. In the testing set, sedimentary pyrite was classified with an accuracy of 100%; however, this result may reflect the limited sample size rather than the model’s true generalization ability and therefore should be interpreted with caution. Feature importance analysis identified Cu, Zn, Te, Bi, and Pb as the key variables of this model. When both trace and rare earth elements (REEs) were used, the detection accuracy for sedimentary pyrite and hydrothermal pyrite in the training set was 87.5% and 100%. However, the combined trace + rare earth elements model exhibited a clear overfitting tendency: its overall training accuracy reached 95.2%, but its validation accuracy (88.9%) was lower than that of the trace-only model (93.8%). Feature importance analysis indicated that Pb, Ho, Zn, Ag, and Ce contribute substantially to the model. The machine learning model proposed in this study is convenient and efficient, providing a novel basis for determining the genetic types of complex pyrite.