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[Display omitted] • A simple (Fe, Mn) or coupled (Cu, Ag coupled with In, Sb, Ga, Ge, Sn) substitution for Zn was observed in sphalerite. • The Zhaxikang is a magmatism-related medium to low-temperature hydrothermal vein deposit. • The sulfur in the Zhaxikang deposit is predominantly sourced from Jurassic marine sulfate or evaporite rocks. • The metals for the Zhaxikang deposit primarily originated from the basement metamorphic rocks (gneiss) of the Greater Himalayan Crystalline complex. The metallogenesis of collisional orogen has been a significant research topic for comprehending the linkage between magmatism, metamorphism, hydrothermalism and ore deposition. In Southern Tibet, the Zhaxikang deposit is a super-large Pb-Zn-Sb-Ag polymetallic deposit with metal reserves of 2.367 Mt Zn + Pb (average grade of 6.43 %), 0.2552 Mt Sb (average grade of 1.14 %), and 2960.6 t Ag (average grade of 101.64 g/t), constituting the largest deposit within North Himalayan Metallogenic Belt. However, the metal sources of the ore-forming material and mineralization process in this deposit remain a subject of controversy due to previous studies primarily relying on a bulk analysis of sulfides, which record the mixed results of multistage mineralization and intergrown minerals of different stages. The objective of this study is to constrain the sources and mineralization process of the Zhaxikang deposit through in-situ analyses of trace elements and sulfur isotopes in sphalerite. Based on ore textures and mineral paragenesis, four mineralization stages and three generations of sphalerite deposited respectively in stage 1 (Sp1), stage 2 (Sp2), and stage 4 (Sp3), were identified. The Pb and Zn mineralization mainly occurred in stage 2, while Sb and Ag were dominantly in stage 4. The trace elements characteristics (Cd, Fe, In, Ga, Ag, Cu, Co, and Mn) observed in sphalerite indicate that the Zhaxikang deposit could be a hydrothermal vein-type deposit associated with magmatism. The δ34S values of sulfides (7.7–18.4 ‰) in the deposit generally exhibit a slight elevation compared to those (4.1–12.9 ‰) of the Jurassic Ridang Formation slate, indicating that the sulfur of the deposit primarily originated from seawater sulfate in the slate through thermochemical sulfate reduction, although a small amount of contribution from mafic rocks also existed in stage 4. The Pb isotopes in stage 2 range from 19.662 to 19.705, 15.852 to 15.865, and 40.214 to 40.283 for the ratios of 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb, respectively, indicating that the metals primarily from the Greater Himalayan Crystalline complex (GHC) with a minor contribution from host rocks. While, the Pb isotopes in stage 4 range from 19.687 to 19.849 for 206Pb/204Pb, from 15.86022 to 15.885 for 207Pb/204Pb, and from 40.261 to 40.414 for 208Pb/204Pb, respectively, indicating that the metals originated from sulfides in the earlier stage as well as the more radiogenic GHC. [ABSTRACT FROM AUTHOR]

[Display omitted] • The Jinding deposit contains high content of associated critical metal Cd, Tl, Ag. • The enrichment of Fe assists incorporation of components Ge + Mn + Pb + As + Tl. • The enrichment of Cd assists incorporation of components Cu + Ag + Sb. • Cd and Fe zonation at sphalerite indicate a potential exploration deposit. The Jinding deposit is well-known to contain high concentrations of metals Zn, Pb, Cd, Tl, Ag, etc. in the world. The associated critical metals and their substitution mechanisms were wildly concerned. This study investigated and compared sphalerites using a combination of textural, trace element, and sulfur isotopic analyses to give insights into element substitution mechanisms and possible sources of ore-forming fluids and to constrain processes involved in ore genesis of the world-class Jinding sediment-hosted Zn-Pb deposit. LA-ICP-MS analyses reveal chemical zoning in the sphalerites together with the coupling of two main groups of trace elements substitution mechanisms: one is Fe + Ge + Mn + Pb + As + Tl and vacancies to substitute Zn, and the other is Cd + Cu + Ag + Sb to substitute Zn. The incorporation of trace elements is facilitated by the replacement of Zn by Cd and Fe. These two group elements have distinct color oscillatory zonation and are intertwined in the trace element LA-ICP-MS element maps. The sulfur isotopic values show high isotope fractionation in the sphalerite from −28.4 to −0.5 ‰, suggesting a bacteriogenic sulfur origin at Jinding. Sphalerite sample has observed that sulfur isotope is correlated with Fe concentration and anti-correlated with Cd concentration. These variations in isotope fractionation and trace element disequilibrium partitioning were interpreted as the effects of temperature and pH with less influence from sulfur activity. These variability zones of sphalerite alternately enriched in Cd- and Fe-related elements suggested that ore fluids may flow from metal-fertile sedimentary/basement sequences during their ascent, and colloform sphalerite was likely formed by a high degree of supercooling, over-saturation, and rapid mixing between bacteriogenic sulfur and metal-rich in spaces of collapse dome. Based on our observations, we suggested that these variability zones of layered sphalerite alternately enriched in Cd and Fe would likely provide useful insight for a potential economic Zn-Pb and associated critical metals mineral exploration deposit. [ABSTRACT FROM AUTHOR]

[Display omitted] • The differences in mineral composition were related to temperature, alteration and hydrothermal fluid. • Ag ranges n*103 ∼ n*104 ppm in galena, n*10 ~ n*103 ppm in sphalerite and pyrite. Sphalerite has higher Au and Ag. • Silver occurs as a solid solution in samples with massive textures and as micro-inclusions in alteration samples. • The minor and trace elements are typical characteristics of massive sulfide deposits in the LSKD. Sphalerite, pyrite and galena are common sulfide minerals in Zn–Pb–(Ag) deposits, containing minor and trace elements that can be used to constrain the ore-forming processes. The Lengshuikeng Ag–Pb–Zn deposit (LSKD) is one of the largest silver deposits in China. The mode of silver occurrence in sulfides remains unclear except for individual silver minerals. In this study, we analyzed the minor and trace element contents of sulfide minerals from massive, vein, and veinlet-disseminated ores by in-situ laser ablation–inductively coupled plasma–mass spectrometry (LA–ICP–MS). The elemental compositions of sulfide minerals are variable. Combining petrographic observations and previous studies, we suggest that the sulfide minerals from two types of mineralization (porphyry and strata-bound types) were formed in a same hydrothermal system, and their content of minor and trace elements mainly is influenced by temperature, alteration of wall rocks and composition change of hydrothermal fluid. The Ag content in galena ranges n*103 ∼ n*104 ppm, whereas that in both sphalerite and pyrite ranges from n*10 ∼ n*103 ppm. Except for galena, a higher content of gold (mean = 0.76 ppm) and silver (mean = 151 ppm) occurs in sphalerite compared with the content of gold (mean = 0.26 ppm) and silver (mean = 69.9 ppm) in pyrite. Generally, altered samples display higher Ag and Au contents in pyrite and sphalerite. Silver occurs in the form of a solid solution in sulfides from samples with massive textures, and as micro-inclusions in sulfides from altered samples. The contents of minor and trace elements (e.g. Cd and In) and their ratios (Ga/In, Zn/Cd and Cd/Fe) are not always sensitive to the temperature and processes of deposit formation. We suggest that sulfides from samples with massive texture and limited alteration are suitable for determining the genetic type of the deposit. Our results show that the hydrothermal fluid is a magmatic fluid related to porphyry granite in the LSKD. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sphalerite chemistry combined with ML methods were used to classify deposit types. • KNN, NN, and RF algorithms are more efficient than other ML methods in the classification tasks. • Ge, Sn, Co, Mn, Ga, and In in sphalerite are the most important discriminant elements. • Binary discrimination diagrams based on PCA and PLS-DA are provided. Sphalerite can form in different geological environments and is the main ore mineral of most Pb-Zn deposits. Trace elements in sphalerite combined with machine learning (ML) methods have been used for deposit type discrimination. However, the performance of different multivariate and ML methods is not systematically compared. Here more than four thousand laser ablation inductively coupled plasma mass spectrometry data from more than one hundred deposits were compiled and investigated by different multivariate and ML methods. Unsupervised multivariate and ML methods including principal component analysis (PCA) and t -distributed stochastic neighbor embedding (t -SNE), and supervised multivariate and ML methods including partial least squares-discriminant analysis (PLS-DA), logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), naïve Bayes (NB), and neural network (NN) are used to classify deposit types. The models are constructed for five deposit types, Mississippi Valley-type (MVT), Volcanogenic Massive Sulfide (VMS), sedimentary exhalative (SEDEX), Epithermal, and Skarn deposits, based on twelve elements in sphalerite, Fe, Pb, Mn, Co, Cu, Ga, Ge, Ag, Cd, In, Sn, and Sb. The PCA and PLS-DA methods show similar clustering results, where Epithermal, MVT, SEDEX, and Skarn deposits can be separated from other deposit types. The t -SNE method is only efficient in discriminating MVT, SEDEX, and Epithermal deposits. The KNN, RF, and NN methods show better performance than LR, SVM, and NB in terms of average accuracy and precision. The PCA, t -SNE, and PLS-DA methods have advantages in data visualization, whereas KNN, NN, and RF methods are more suitable for classification tasks. Feature importance analyses of the PLS-DA and RF methods show that the most important discriminant elements in the classification are Ge, Mn, In, Sn, Ga, and Sb. The models based on PCA, PLS-DA, KNN, NN, and RF are used to predict sphalerite samples with uncertain origins. All the models give similar classification results for deposit types, which are consistent with the ore-forming geological setting. The multivariate and ML models, including discrimination diagrams of PCA and PLS-DA, can be used as the first screening for the type of Pb-Zn mineralization in mineral exploration. [ABSTRACT FROM AUTHOR]