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Genesis of the Ulaan silver-lead–zinc deposit in Northeast Mongolia: Constraints from S and Pb isotopes, together with U-Pb and Rb-Sr geochronology 蒙古东北部乌兰银铅锌矿床的成因:来自S和Pb同位素以及U-Pb和Rb-Sr地质年代学的制约因素
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106262
Taotao Wu , Chunji Xue , Yongheng Zhou , Lu Chai , Qingshuang Wang , Qingzhong Bao
The Ulaan silver-lead–zinc deposit (hereinafter referred to as the Ulaan deposit) is identified as the largest silver-lead–zinc polymetallic deposit in Mongolia, with proved reserves including 2,240 tons of silver (Ag; average grade: 49 g/t), 440,000 tons of lead (Pb; average grade: 1.13 %), and 810,000 tons of zinc (Zn; average grade: 2.07 %). However, the genesis of this deposit remains unclear. The Ag-Pb-Zn ore bodies in the deposit, occurring as cylinders in shape within the Middle-Late Jurassic rhyolites, are governed by a concealed breccia pipe. The ore minerals include galena, sphalerite, and pyrite, followed by chalcopyrite, hematite, stibnite, and siderite. The primary alterations of the surrounding rocks include silicification, chloritization, kaolinization, argillization, carbonatization, and skarnization. The Rb-Sr dating of sulfide minerals and associated vein minerals in the ores yielded isochron ages varying in a range of 146 ± 3 Ma (n = 6, MSWD=1.3), suggesting mineralization during the Late Jurassic. The δ34S values of sulfide minerals in the ores range from 1.6 ‰ to 4.3 ‰, suggesting that the sulfur originated primarily from magmas or deep sources. The isotopic compositions of coexisting sphalerite-galena minerals in the deposit revealed mineralization temperature estimates ranging between 331 °C and 449 °C, indicating a medium- to high-temperature ore-forming conditions. The sulfide minerals exhibit 208Pb/204Pb ratios ranging from 38.138 to 38.301, 207Pb/204Pb ratios from 15.543 to 15.594, and 206Pb/204Pb ratios from 18.318 to 18.354, suggesting that ore-forming metals, represented by Pb, also originated primarily from mantle source. The zircon U-Pb dating of rhyolites in the ore-hosting strata and ore-controlling breccia pipes yielded ages of 160.6 ± 1.7 Ma (n = 24, MSWD=0.68) and 161.6 ± 1.6 Ma (n = 30, MSWD=0.89), respectively, indicating volcanic eruptions during the early Late Jurassic. These ore-hosting rhyolites exhibit characteristics of A-type rhyolites, suggesting that they were formed in an intracontinental extensional environment. These rhyolites share similar rare earth element (REE) distribution patterns with fluorite formed in the main mineralization stage, suggesting a genetic link between the mineralization and magmatic processes. This study proposes that the Ulaan deposit was a hydrothermal deposit formed in an extensional environment following the closure of the Mongol-Okhotsk Ocean, with ore-forming metals and hydrothermal fluids associated with volcanic rocks or magmatic-hydrothermal processes.
乌兰银铅锌矿床(以下简称乌兰矿床)被认定为蒙古最大的银铅锌多金属矿床,探明储量包括 2240 吨银(Ag;平均品位:49 克/吨)、44 万吨铅(Pb;平均品位:1.13%)和 81 万吨锌(Zn;平均品位:2.07%)。然而,该矿床的成因仍不清楚。该矿床中的银铅锌矿体呈圆柱形,位于中-晚侏罗世流纹岩中,由一个隐蔽的角砾岩管控制。矿石矿物包括方铅矿、闪锌矿和黄铁矿,其次是黄铜矿、赤铁矿、闪锌矿和菱铁矿。周围岩石的主要蚀变包括硅化、绿泥石化、高岭土化、芒硝化、碳酸盐化和矽卡岩化。对矿石中的硫化物矿物和相关脉石矿物进行的铷-锶定年测定得出的等时线年龄在 146 ± 3 Ma 之间(n = 6,MSWD=1.3),表明矿化过程发生在晚侏罗世。矿石中硫化物矿物的δ34S值在1.6‰到4.3‰之间,表明硫主要来源于岩浆或深部来源。矿床中共生闪锌矿-方铅矿矿物的同位素组成显示,成矿温度估计在 331 ℃ 至 449 ℃ 之间,表明成矿条件为中高温。硫化物矿物的 208Pb/204Pb 比值范围为 38.138 至 38.301,207Pb/204Pb 比值范围为 15.543 至 15.594,206Pb/204Pb 比值范围为 18.318 至 18.354,表明以 Pb 为代表的成矿金属也主要来源于地幔。对成矿地层和控矿角砾岩管中的流纹岩进行的锆石U-Pb测年显示,其年龄分别为160.6 ± 1.7 Ma(n = 24,MSWD=0.68)和161.6 ± 1.6 Ma(n = 30,MSWD=0.89),表明在晚侏罗世早期有火山喷发。这些矿床流纹岩表现出 A 型流纹岩的特征,表明它们是在大陆内部延伸环境中形成的。这些流纹岩与主要成矿阶段形成的萤石具有相似的稀土元素(REE)分布模式,表明成矿与岩浆过程之间存在遗传联系。本研究提出,乌兰矿床是蒙古-奥霍次克洋关闭后在伸展环境中形成的热液矿床,成矿金属和热液与火山岩或岩浆-热液过程有关。
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引用次数: 0
Characteristics of antimony mineralization in the Yangla polymetallic deposit, northwestern Yunnan, SW China: Insights from calcite Sm-Nd dating and C-O-Sr isotopes 中国西南部云南西北部羊拉多金属矿床锑矿化特征:方解石 Sm-Nd 测定和 C-O-Sr 同位素的启示
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106266
Xinfu Wang , Bo Li , Shucheng Tan , Guo Tang , Zuopeng Xiang , Yuedong Liu
Calcite is the main gangue mineral in antimony (Sb) deposits, and its compositions can reflect the physicochemical conditions of Sb mineralization. The Yangla is the largest Sb deposit (10 kt Sb @ 14.87 %) in the Jinshajiang suture zone (SW China), and the lode-type Sb orebodies are stratabound or developed along NE-trending fracture zones in marble. To constrain the time of Sb mineralization and establish any genetic link with the local magmatism and wallrocks, we performed calcite Sm-Nd dating and bulk C-O and in-situ Sr isotope analyses. The results show that the Sb mineralization (∼155 Ma) was considerably younger than the Cu-Pb-Zn mineralization (∼230 Ma), skarn alteration (∼234 Ma), and granitoid emplacement (∼230 Ma) at Yangla, but much older than the local W mineralization (∼30 Ma). The initial 87Sr/86Sr ratio of calcite (0.71972–0.72208) is much higher than that of the Triassic granodiorite (0.71149– 0.71990) and Carboniferous basalt (0.70562–0.70995), suggesting mixed source of calcite from the ore fluids and Devonian wallrocks. The ore-related calcite has δ13CPDB (−4.53 to − 2.33 ‰) and δ18OSMOW (+14.98 to + 16.30 ‰) values that fall between the granite and marine carbonate isotopic fields. This suggests that the ore-forming fluid may be related to the low-temperature alteration of granites and marine carbonate dissolution. Simulated precipitation temperature calculation for the ore-related calcite yielded 200–150 °C, and the calcite C-O isotopes suggest that fluid mixing, fluid-rock interactions, and CO2 degassing may have precipitated the stibnite in the fracture zones under low-temperature conditions. Our new geochemical results and published data suggest that the Yangla polymetallic mineralization was multiphase, comprising the Indosinian Cu-Pb-Zn (∼230 Ma), Yanshanian Sb (∼155 Ma), and Himalayan W-Sb (∼30 Ma) metallogenic events.
方解石是锑(Sb)矿床的主要煤矸石矿物,其成分可反映锑矿化的物理化学条件。羊拉锑矿是金沙江缝合带(中国西南部)最大的锑矿床(10 kt Sb @ 14.87 %),锭型锑矿体在大理岩中呈层状或沿东北向断裂带发育。为了确定锑成矿的时间,并建立与当地岩浆岩和壁岩之间的遗传联系,我们进行了方解石 Sm-Nd 测定以及大块 C-O 和原位 Sr 同位素分析。结果表明,锑矿化(155Ma∼)比羊拉的铜铅锌矿化(230Ma∼)、矽卡岩蚀变(234Ma∼)和花岗岩成岩(230Ma∼)要年轻得多,但比当地的钨矿化(30Ma∼)要早得多。方解石的初始87Sr/86Sr比值(0.71972-0.72208)远高于三叠系花岗闪长岩(0.71149-0.71990)和石炭纪玄武岩(0.70562-0.70995),表明方解石来源于矿液和泥盆纪岩壁。与矿石相关的方解石的δ13CPDB(-4.53 至 -2.33‰)和δ18OSMOW(+14.98 至 +16.30‰)值介于花岗岩和海洋碳酸盐同位素场之间。这表明成矿流体可能与花岗岩低温蚀变和海相碳酸盐溶解有关。与矿石有关的方解石的模拟沉淀温度计算结果为 200-150 °C,方解石的 C-O 同位素表明,流体混合、流体-岩石相互作用和二氧化碳脱气可能在低温条件下沉淀了断裂带中的闪长岩。我们新的地球化学结果和已发表的数据表明,羊拉多金属成矿作用是多相的,包括印支期铜-铅-锌(230 Ma∼)、燕山期锑(155 Ma∼)和喜马拉雅W-锑(30 Ma∼)成矿事件。
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引用次数: 0
Geochronology, in-situ elements and sulfur isotopes of sulfides from the Songjiashan cobalt-iron deposit in the Zhongtiao mountains of North China Craton: Implications for cobalt occurrence and ore genesis 华北克拉通中条山宋家山钴铁矿床硫化物的地质年代、原位元素和硫同位素:对钴成矿和矿石成因的启示
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106265
Wen Li , Bingyu Gao , Caiyun Lan , Brendan A. Bishop , Wenjun Li , Xin Zhang , Changle Wang , Lingang Xu , Lianchang Zhang
The Songjiashan Co-Fe deposit in the central part of the “Tongshan skylight” on the southeastern edge of the Zhongtiao Mountains is hosted by the volcanic-sedimentary rock series of the Paleoproterozoic Songjiashan Group. The spatial distribution of the orebodies is controlled by south-north trending rock units. Based on microscopic observations, the dominant ore minerals included magnetite, pyrite, chalcopyrite, carrollite, and linnaeite, while gangue minerals comprised quartz, calcite, sericite, and chlorite. Cobalt-iron ores had massive, banded, disseminated, and veinlet texture, and alteration of the host rocks included silicification, sericitization, pyritization, carbonation, and chloritization. Mineralization processes of the Songjiashan deposit were grouped into three periods: sedimentation, metamorphism, and hydrothermal. The Co concentrations in hydrothermal pyrite (Py-III) varied from 1.05 % to 3.75 %, with an average of 2.45 %. Cobalt in pyrite was homogeneously distributed and inversely correlated to Fe, indicating that Co isomorphically replaced Fe in pyrite. The characteristic Co/Ni ratio of pyrite varied greatly, ranging from 0.1 to 1000, reflecting various genetic types of sedimentation, metamorphism, and hydrothermal mineralization, with the main mineralization period primarily related to hydrothermal activities. Zircon U-Pb geochronology of the host rock and Re-Os isochron of Co-bearing pyrites indicate that Co mineralization mainly occurred at ∼2100 Ma. In-situ S isotopic analysis of sulfides reveals two peak δ34S values of 5–9 ‰ and 12–16 ‰. We interpret that the former value reflects the mixing of volcanic and marine sulfate sources, while the latter value is mainly artributted to marine sulfate sources. All δ34S values were lower than those of Proterozoic marine sulfates (15–20 ‰). Accordingly, we infer that thermochemical sulfate reduction plays a key role in marine sulfate reduction, and that the formation of Co-rich ore bodies in the Songjiashan deposit have undergone processes of initial sedimentation, metamorphism-deformation, and subsequent hydrothermal overprinting. Genetically, we suggest that the Songjiashan deposit belongs to a sedimentary-metamorphic hydrothermal superposition type Co-Fe deposit.
宋家山 Co-Fe 矿床位于中条山东南边缘 "铜山天窗 "的中部,赋存于古新生代宋家山组的火山-沉积岩系中。矿体的空间分布受南北走向岩石单元的控制。根据显微观察,主要矿石矿物包括磁铁矿、黄铁矿、黄铜矿、卡罗来石和菱铁矿,而煤矸石矿物包括石英、方解石、绢云母和绿泥石。钴铁矿石具有块状、条带状、散布状和细脉状的质地,母岩的蚀变包括硅化、绢云母化、黄铁矿化、碳酸盐化和绿泥石化。宋家山矿床的成矿过程分为三个时期:沉积期、变质期和热液期。热液黄铁矿(Py-III)中的钴含量从1.05%到3.75%不等,平均为2.45%。黄铁矿中的钴分布均匀,且与铁成反比,表明黄铁矿中的钴同构取代了铁。黄铁矿的特征钴/镍比变化很大,从 0.1 到 1000 不等,反映了沉积、变质和热液成矿的各种成因类型,主要成矿期主要与热液活动有关。主岩的锆石U-Pb地质年代和含钴黄铁矿的Re-Os等时线表明,钴矿化主要发生在2100Ma∼。硫化物的原位 S 同位素分析显示了两个峰值 δ34S 值,分别为 5-9 ‰ 和 12-16‰。我们认为前一个值反映了火山和海洋硫酸盐源的混合,而后一个值则主要归因于海洋硫酸盐源。所有δ34S值均低于新生代海相硫酸盐的值(15-20‰)。据此,我们推断热化学硫酸盐还原在海相硫酸盐还原中起着关键作用,宋家山矿床富钴矿体的形成经历了初始沉积、变质-变形、热液叠印等过程。从成因上看,我们认为宋家山矿床属于沉积-变质热液叠加型Co-Fe矿床。
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引用次数: 0
Genesis of the Longfengchang polymetallic sulfide deposit in the southwest Fujian depression, southeast China, with a comparative study of the “Makeng-Type” iron deposit 中国东南部闽西南坳陷龙凤场多金属硫化物矿床成因及 "马坑型 "铁矿床比较研究
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106271
Qiang Wang , Hongxin Fan , Xiangdie Cui , Yulong Yang , Siyue Yao , Fengchun Li , Huimin Zhang
The Southwest Fujian Depression Belt is a prominent metallogenic zone for skarn-type iron polymetallic deposits in China, with the Longfengchang (LFC) sulfur polymetallic deposit representing a medium-scale, sulfide-dominated deposit in this region. This study conducted a detailed analysis of the LFC deposit, focusing on its mineralogy, mineral composition, and in-situ sulfur isotopes, alongside a comparative study with the “Makeng-type” deposit. The study aims to elucidate the genesis of the LFC deposit, its relationship with the “Makeng-type” deposit, and the factors underlying differences in dominant economic minerals and resource scale. The LFC deposit is hosted within the skarn above the fault contact zone between the Lindi Formation sandstone and the Chuanshan–Qixia Formation carbonate, with mineralization stages classified as skarn-magnetite, quartz-sulfide, and carbonate. LFC garnets are primarily composed of CaO, TFeO, and SiO2, with minor Al2O3 and trace amounts of MgO and MnO, classifying them as distal exoskarn andradite. The presence of Mn3+ substituting for Fe3+ in garnet suggests that the ore-forming fluid during the garnet skarn stage was likely oxidizing and weakly acidic. LFC pyrites exhibit Co/Ni ratios primarily ranging from 1 to 10, decreasing from Py1 to Py3. In-situ sulfur isotope δ34S values range from −1.48 to 3.51 ‰, centering around 0 ‰, and increase from Py1 to Py3, suggesting a magmatic-hydrothermal origin and a cooling metallogenic process. Thus, the LFC deposit is classified as a magmatic-hydrothermal skarn-type deposit, consistent with the genesis of “Makeng-type” deposits. The absence of the Jinshe Formation, and mantle-derived magma contribution, and less developed “Si-Ca” interface may explain the smaller scale and different mineralization type in the LFC deposit compared to the “Makeng-type” deposit. The key prospecting area for large iron-sulfur polymetallic deposits in the Southwest Fujian Depression Belt should feature a nappe structural window, well-preserved Jinshe Formation, developed “Si-Ca” interface, Yanshanian high-K calc-alkaline to shoshonitic intrusions, and coeval mantle-derived magma.
闽西南凹陷带是中国矽卡岩型铁多金属矿床的重要成矿带,其中龙凤场硫多金属矿床是该地区以硫化物为主的中型矿床。本研究对龙凤场硫多金属矿床进行了详细分析,重点关注其矿物学、矿物组成和原位硫同位素,并与 "马坑型 "矿床进行了对比研究。该研究旨在阐明 LFC 矿床的成因、它与 "Makeng 型 "矿床的关系,以及造成主要经济矿物和资源规模差异的因素。LFC 矿床赋存于林地层砂岩与穿山-栖霞层碳酸盐岩断层接触带上方的矽卡岩中,成矿阶段分为矽卡岩-磁铁矿、石英-硫化物和碳酸盐岩。LFC 石榴石的主要成分是 CaO、TFeO 和 SiO2,还有少量 Al2O3 以及微量的 MgO 和 MnO,因此被归类为远期外矽卡岩和斜长石。石榴石中 Mn3+ 替代 Fe3+ 的存在表明,石榴石矽卡岩阶段的成矿流体很可能是氧化性和弱酸性的。LFC 黄铁矿的钴/镍比值主要在 1 到 10 之间,从 Py1 到 Py3 依次降低。原位硫同位素δ34S值范围在-1.48到3.51‰之间,以0‰为中心,从Py1到Py3依次增大,这表明了岩浆-热液成因和冷却成矿过程。因此,LFC矿床属于岩浆-热液矽卡岩型矿床,与 "马坑型 "矿床的成因一致。与 "Makeng 型 "矿床相比,LFC 矿床规模较小,成矿类型不同,其原因可能是没有金社地层和地幔岩浆的贡献,以及 "Si-Ca "界面不发达。闽西南凹陷带大型铁硫多金属矿床的重点找矿区域应具有岩浆构造窗口、保存完好的金畲地层、发育的 "Si-Ca "界面、燕山期高K钙碱性至闪长岩侵入体以及共生的地幔源岩浆。
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引用次数: 0
Corrigendum to “Application of (U-Th)/He hematite geochronology to the Çaldağ lateritic Ni-Co deposit, Western Anatolia: Implications for multi-stage weathering events during interglacial periods/segments” [Ore Geology Reviews 172 (2024) 106203] (U-Th)/He赤铁矿地质年代学在安纳托利亚西部Çaldağ红土镍钴矿床的应用:对冰期/冰段多阶段风化事件的影响" [Ore Geology Reviews 172 (2024) 106203] 的更正
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106223
Nilay Gülyüz , İlkay Kuşcu , Martin Danišík
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引用次数: 0
The occurrence of cobaltite nanoparticles in pyrite from the De’erni deposit, NW China 中国西北部德尔尼矿床黄铁矿中钴纳米颗粒的出现
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106268
Lei Yan , Xianzheng Guo , Yu Fan , Jun Huang , Tong Zuo , Taofa Zhou
Cobalt (Co) is a critical metal that occurs in many types of deposits, Co minerals and sulfide hosts are the main forms of Co occurrence. Pyrite is the most important cobalt-bearing mineral in the De’erni Cu-Zn-Co ultramafic-hosted volcanogenic massive sulfide deposits. However, the occurrence and enrichment of Co in pyrite remain unclear. In this study, a combination of LA-ICP-MS and STEM techniques was employed to conduct a detailed mineralogical investigation of pyrite in the De’erni deposit. The results revealed significant variations in cobalt content among pyrite samples from different mineral assemblages. Pyrite associated with magnetite (Mag), pyrrhotite (Po), chalcopyrite (Ccp), arsenopyrite (Apy), and bornite (Bn) (Py-Mag-Po-Ccp-Apy-Bn suite of mineral assemblages) exhibited the highest cobalt content, which ranged from 672.6 ppm to 2007 ppm. Cobalt occurs in two forms in the pyrite from the De’erni deposit: as cobaltite nanoparticles (NPs) and as a substitute for iron (Fe) in the pyrite lattice. The enrichment mechanism of cobalt in pyrite was explored at the deposit and mineral scales. The results indicate that a decrease in ore-forming fluid temperature and an increase in cobalt content may be significant factors contributing to cobalt enrichment at the deposit scale. Lattice defects may play a crucial role in cobalt enrichment within the pyrite lattice. Furthermore, the discovery of cobaltite NPs in pyrite could provide new insights for explaining the complex zonation of the cobalt element in pyrite.
钴(Co)是一种重要的金属,存在于许多类型的矿床中,钴矿物和硫化物矿床是钴的主要存在形式。黄铁矿是 De'eri 铜锌钴超基性火山成因块状硫化物矿床中最重要的含钴矿物。然而,黄铁矿中钴的存在和富集情况仍不清楚。在本研究中,结合使用了 LA-ICP-MS 和 STEM 技术,对 De'erni 矿床中的黄铁矿进行了详细的矿物学研究。结果表明,不同矿物组合的黄铁矿样品中钴含量差异很大。与磁铁矿(Mag)、黄铁矿(Po)、黄铜矿(Ccp)、黄砷矿(Apy)和透辉石(Bn)(Py-Mag-Po-Ccp-Apy-Bn 矿物组合)伴生的黄铁矿钴含量最高,从 672.6 ppm 到 2007 ppm 不等。钴以两种形式存在于 De'erni 矿床的黄铁矿中:钴矿纳米颗粒(NPs)和黄铁矿晶格中铁(Fe)的替代物。在矿床和矿物尺度上探索了黄铁矿中钴的富集机制。结果表明,成矿流体温度的降低和钴含量的增加可能是矿床尺度上钴富集的重要因素。晶格缺陷可能对黄铁矿晶格内的钴富集起着关键作用。此外,在黄铁矿中发现钴铁NPs可为解释黄铁矿中钴元素的复杂分带提供新的见解。
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引用次数: 0
Tourmaline geochemical and B isotopic constraints on pegmatite Li mineralization and exploration 电气石地球化学和 B 同位素对伟晶岩锂矿化和勘探的制约作用
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106257
Yang Sun , Bin Chen , Wen-Jing Li , Shuai-Jie Liu
Pegmatite–related deposits represent one of the most significant types of mineral deposits housing rare–metal elements such as Li, Be, Nb, Ta, Rb, Cs, and Sn. Although extensively studied for almost two centuries, the mechanism controlling the rare–metal mineralization in pegmatites remains controversial. In addition to the enrichment of rare–metal elements in the source region, differentiation processes (e.g., fractional crystallization and liquid immiscibility) after emplacement may have also contributed to the concentration and mineralization of rare–metal elements. However, compared to fractional crystallization, the role of liquid immiscibility in pegmatite mineralization has received limited attention. In this study, the element and boron (B) isotopic compositions of tourmalines from different textural zones (Zones I–VI) of the rare–metal–mineralized Koktokay No. 3 pegmatite, Altai, NW China, as well as from the altered country rock and the border zone, were analyzed to evaluate the role of liquid immiscibility in the generation of Li–mineralized pegmatites. Tourmalines display a variety of compositions, ranging from schorl and elbaite in the outer zones to elbaite in the inner zones of the Koktokay No. 3 pegmatite. Tourmalines from Zones I–III exhibit no obvious internal textures, whereas some tourmalines from Zones IV–VI have replacement textures or abrupt zonations. The distinction is attributed to the absence and presence of exsolving fluids during their formation, respectively. Tourmalines in Zones I–III and VII–VIII display less variable δ11B values (–15.07 ‰ to –12.21 ‰ and –14.16 ‰ to –13.10 ‰, respectively), reflecting a negligible B isotope fractionation produced by fractional crystallization during the pegmatite evolution. By contrast, tourmalines in Zones IV–VII exhibit more significant variations in δ11B values (–14.83 ‰ to –8.09 ‰) compared to those in Zones I–III and VII–VIII. The high δ11B tourmalines in Zones IV–VII were most likely crystallized from the fluids exsolving from the highly evolved pegmatite–forming magma. Their occurrence indicates the fluid exsolution occurring between zones IV and V, where Li mineralization began in the Koktokay No. 3 pegmatite. The mineralization of rare–metal elements is closely linked to the evolution of magma into a coexisting magma–fluid system. In addition, Li–mineralized pegmatites are characterized by tourmalines with Fe3+Al-1 substitution and higher Zn, Li, Li/Sr, and V/Sc than barren pegmatites. These differences are believed to be due to the higher fO2 and greater extent of magmatic differentiation in Li–mineralized pegmatites compared to the barren ones. These findings provide new insights into using the geochemical compositions of tourmalines as a guide for exploring Li–mineralized pegmatites.
伟晶岩相关矿床是含有稀有金属元素(如锂、铍、铌、钽、铷、铯和锡)的最重要矿床类型之一。尽管近两个世纪以来对伟晶岩中稀有金属成矿机制进行了广泛研究,但仍存在争议。除了源区的稀有金属元素富集外,成岩后的分异过程(如点状结晶和液态不溶性)也可能促成了稀有金属元素的富集和矿化。然而,与点状结晶相比,液态不溶性在伟晶岩成矿过程中的作用受到的关注有限。本研究分析了中国西北部阿尔泰稀有金属矿化科克托卡伊三号伟晶岩不同纹理区(I-VI区)以及蚀变乡村岩和边界区的电气石的元素和硼(B)同位素组成,以评估液态不溶性在锂矿化伟晶岩生成过程中的作用。電氣石顯示出多種不同的成分,從外圍區域的矽卡岩和白雲母,到可克托凱三號偉晶岩內側區域的白雲母,不一而足。I 至 III 區域的電氣石並沒有明顯的內部紋理,而 IV 至 VI 區域的一些電氣石則具有置換紋理或突兀的分帶。這分別是由於電氣石在形成時沒有或有溶出流體所致。I-III及VII-VIII區域的電氣石的δ11B值變化較小(分別為-15.07‰至-12.21‰及-14.16‰至-13.10‰),反映在偉晶岩演變過程中,由分形結晶所產生的B同位素分馏可忽略不计。相比之下,第四至第七區的電氣石的δ11B值(-14.83 ‰至-8.09 ‰)的變化較第一至第三區和第七至第八區的電氣石顯示得更為顯著。第四至第七區的高δ11B電氣石很可能是由高度演變的偉晶岩形成岩漿所流出的流體結晶而成。它们的出现表明,流体溶解发生在 IV 区和 V 区之间,而 Koktokay 3 号伟晶岩的锂矿化就是从这里开始的。稀有金属元素的成矿与岩浆演变为岩浆-流体共存系统密切相关。此外,与贫瘠伟晶岩相比,锂矿化伟晶岩的特征是具有 Fe3+Al-1 置换的电气石和较高的锌、锂、锂/Sr 和 V/Sc。这些差异被认为是由于锂矿化伟晶岩与贫瘠伟晶岩相比具有更高的 fO2 和更大的岩浆分异程度。这些发现为利用电气石的地球化学成分作为勘探锂矿化伟晶岩的指南提供了新的见解。
{"title":"Tourmaline geochemical and B isotopic constraints on pegmatite Li mineralization and exploration","authors":"Yang Sun ,&nbsp;Bin Chen ,&nbsp;Wen-Jing Li ,&nbsp;Shuai-Jie Liu","doi":"10.1016/j.oregeorev.2024.106257","DOIUrl":"10.1016/j.oregeorev.2024.106257","url":null,"abstract":"<div><div>Pegmatite–related deposits represent one of the most significant types of mineral deposits housing rare–metal elements such as Li, Be, Nb, Ta, Rb, Cs, and Sn. Although extensively studied for almost two centuries, the mechanism controlling the rare–metal mineralization in pegmatites remains controversial. In addition to the enrichment of rare–metal elements in the source region, differentiation processes (e.g., fractional crystallization and liquid immiscibility) after emplacement may have also contributed to the concentration and mineralization of rare–metal elements. However, compared to fractional crystallization, the role of liquid immiscibility in pegmatite mineralization has received limited attention. In this study, the element and boron (B) isotopic compositions of tourmalines from different textural zones (Zones I–VI) of the rare–metal–mineralized Koktokay No. 3 pegmatite, Altai, NW China, as well as from the altered country rock and the border zone, were analyzed to evaluate the role of liquid immiscibility in the generation of Li–mineralized pegmatites. Tourmalines display a variety of compositions, ranging from schorl and elbaite in the outer zones to elbaite in the inner zones of the Koktokay No. 3 pegmatite. Tourmalines from Zones I–III exhibit no obvious internal textures, whereas some tourmalines from Zones IV–VI have replacement textures or abrupt zonations. The distinction is attributed to the absence and presence of exsolving fluids during their formation, respectively. Tourmalines in Zones I–III and VII–VIII display less variable δ<sup>11</sup>B values (–15.07 ‰ to –12.21 ‰ and –14.16 ‰ to –13.10 ‰, respectively), reflecting a negligible B isotope fractionation produced by fractional crystallization during the pegmatite evolution. By contrast, tourmalines in Zones IV–VII exhibit more significant variations in δ<sup>11</sup>B values (–14.83 ‰ to –8.09 ‰) compared to those in Zones I–III and VII–VIII. The high δ<sup>11</sup>B tourmalines in Zones IV–VII were most likely crystallized from the fluids exsolving from the highly evolved pegmatite–forming magma. Their occurrence indicates the fluid exsolution occurring between zones IV and V, where Li mineralization began in the Koktokay No. 3 pegmatite. The mineralization of rare–metal elements is closely linked to the evolution of magma into a coexisting magma–fluid system. In addition, Li–mineralized pegmatites are characterized by tourmalines with Fe<sup>3+</sup>Al<sub>-1</sub> substitution and higher Zn, Li, Li/Sr, and V/Sc than barren pegmatites. These differences are believed to be due to the higher <em>f</em>O<sub>2</sub> and greater extent of magmatic differentiation in Li–mineralized pegmatites compared to the barren ones. These findings provide new insights into using the geochemical compositions of tourmalines as a guide for exploring Li–mineralized pegmatites.</div></div>","PeriodicalId":19644,"journal":{"name":"Ore Geology Reviews","volume":"173 ","pages":"Article 106257"},"PeriodicalIF":3.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Semi-supervised graph convolutional networks for integrating continuous and binary evidential layers for mineral exploration targeting 用于整合连续和二进制证据层的半监督图卷积网络,以确定矿产勘探目标
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106260
Yongliang Chen , Bowen Chen , Alina Shaylan
<div><div>Effectively integrating evidential layers of different data types from multi-disciplinary geosciences to predict mineral prospecting targets is the crucial step for mineral exploration. Because the commonly used evidential layer integration method, such as statistical methods and machine learning methods, can only deal with the evidential layers of the same data type, divergent data types must be transformed into the same data type that the evidential layer integrating method can handle. However, the data type transformation inevitably results in the loss of some information in the original data type. To solve this problem, a semi-supervised graph convolutional networks (SSGCN) for graph-structured data classification in machine learning field was adopted to integrate binary and continuous evidential layers to predict mineral prospecting targets. A case study of mineral exploration targeting was carried out in the Lalingzaohuo area, Qinghai Province, China. The mineral exploration data collected during the 1:50,000 geological survey was used to train a SSGCN classification model to predict polymetallic prospecting targets. The input graph-structured data of the SSGCN model is composed of an adjacency matrix and a feature matrix. To test whether a high-performance SSGCN classification model can be established for integrating continuous and binary evidential layers in mineral exploration targeting, in this study, the adjacency and feature matrices were constructed using (<em>a</em>) continuous geochemical evidential layers, (<em>b</em>) binary geological and geophysical evidential layers, (<em>c</em>) binary geological, geophysical and geochemical evidential layers, (<em>d</em>) continuous geochemical evidential layers and binary geological and geophysical evidential layers, (<em>e</em>) continuous geochemical evidential layers and binary geological, geophysical and geochemical evidential layers, and (<em>f</em>) binary geological, geophysical, geochemical evidential layers and continuous geochemical evidential layers. Accordingly, the six SSGCN models were built and used to predict polymetallic prospecting targets. In terms of the receiver operating characteristic (ROC) curves, the performances of the six SSGCN models from high to low are, respectively, models (<em>e</em>) (<em>c</em>), (<em>d</em>), (<em>a</em>), (<em>f</em>) and (<em>b</em>). The area under the ROC curves of the six SSGCN models from high to low are, respectively, (<em>e</em>) 0.9489, (<em>c</em>) 0.9457, (<em>d</em>) 9080, (<em>a</em>) 0.9039, (<em>f</em>) 0.8717 and (<em>b</em>) 0.8453. The polymetallic prospecting targets predicted by the six SSGCN models occupy, respectively, 22.43 %, 8.12 %, 12.93 %, 7.99 %, 7.60 %, 24.16 % of the study area; and correctly classified known polymetallic deposits are, respectively, 88 %, 71 %, 88 %, 82 %, 88 % and 88 %. These results show that the SSGCN model performs best in predicting polymetallic prospecting targets when the cont
有效整合多学科地球科学不同数据类型的证据层来预测找矿目标是矿产勘探的关键步骤。由于常用的证据层整合方法,如统计方法和机器学习方法,只能处理相同数据类型的证据层,因此必须将不同数据类型转化为证据层整合方法所能处理的相同数据类型。然而,数据类型转换不可避免地会导致原数据类型中某些信息的丢失。为了解决这个问题,我们采用了机器学习领域中用于图结构数据分类的半监督图卷积网络(SSGCN)来整合二进制和连续证据层,从而预测找矿目标。在中国青海省拉林措霍地区开展了一项矿产勘探目标定位案例研究。在 1:50,000 地质调查中收集的矿产勘探数据被用于训练 SSGCN 分类模型,以预测多金属找矿靶区。SSGCN 模型的输入图结构数据由邻接矩阵和特征矩阵组成。为了测试能否建立一个高性能的 SSGCN 分类模型,以整合矿产勘探目标中的连续和二元证据层,本研究使用以下数据构建了邻接矩阵和特征矩阵:(a) 连续地球化学证据层;(b) 二元地质和地球物理证据层;(c) 二元地质、地球物理和地球化学证据层、(d) 连续地球化学证据层和二元地质和地球物理证据层,(e) 连续地球化学证据层和二元地质、地球物理和地球化学证据层,以及 (f) 二元地质、地球物理、地球化学证据层和连续地球化学证据层。据此,建立了六个 SSGCN 模型,用于预测多金属找矿靶区。从接收者操作特征曲线(ROC)来看,六个 SSGCN 模型的性能从高到低分别为模型(e)(c)、(d)、(a)、(f)和(b)。六个 SSGCN 模型的 ROC 曲线下面积从高到低分别为(e)0.9489、(c)0.9457、(d)9080、(a)0.9039、(f)0.8717 和(b)0.8453。六个 SSGCN 模型预测的多金属找矿靶区分别占研究区面积的 22.43%、8.12%、12.93%、7.99%、7.60% 和 24.16%;已知多金属矿床的正确分类率分别为 88%、71%、88%、82%、88% 和 88%。这些结果表明,当使用连续地球化学证据层构建邻接矩阵,使用二元地质、地球物理和地球化学证据层构建特征矩阵时,SSGCN 模型在预测多金属找矿目标方面表现最佳。因此,使用 SSGCN 算法整合连续和二元证据层来预测找矿目标是可行的。
{"title":"Semi-supervised graph convolutional networks for integrating continuous and binary evidential layers for mineral exploration targeting","authors":"Yongliang Chen ,&nbsp;Bowen Chen ,&nbsp;Alina Shaylan","doi":"10.1016/j.oregeorev.2024.106260","DOIUrl":"10.1016/j.oregeorev.2024.106260","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Effectively integrating evidential layers of different data types from multi-disciplinary geosciences to predict mineral prospecting targets is the crucial step for mineral exploration. Because the commonly used evidential layer integration method, such as statistical methods and machine learning methods, can only deal with the evidential layers of the same data type, divergent data types must be transformed into the same data type that the evidential layer integrating method can handle. However, the data type transformation inevitably results in the loss of some information in the original data type. To solve this problem, a semi-supervised graph convolutional networks (SSGCN) for graph-structured data classification in machine learning field was adopted to integrate binary and continuous evidential layers to predict mineral prospecting targets. A case study of mineral exploration targeting was carried out in the Lalingzaohuo area, Qinghai Province, China. The mineral exploration data collected during the 1:50,000 geological survey was used to train a SSGCN classification model to predict polymetallic prospecting targets. The input graph-structured data of the SSGCN model is composed of an adjacency matrix and a feature matrix. To test whether a high-performance SSGCN classification model can be established for integrating continuous and binary evidential layers in mineral exploration targeting, in this study, the adjacency and feature matrices were constructed using (&lt;em&gt;a&lt;/em&gt;) continuous geochemical evidential layers, (&lt;em&gt;b&lt;/em&gt;) binary geological and geophysical evidential layers, (&lt;em&gt;c&lt;/em&gt;) binary geological, geophysical and geochemical evidential layers, (&lt;em&gt;d&lt;/em&gt;) continuous geochemical evidential layers and binary geological and geophysical evidential layers, (&lt;em&gt;e&lt;/em&gt;) continuous geochemical evidential layers and binary geological, geophysical and geochemical evidential layers, and (&lt;em&gt;f&lt;/em&gt;) binary geological, geophysical, geochemical evidential layers and continuous geochemical evidential layers. Accordingly, the six SSGCN models were built and used to predict polymetallic prospecting targets. In terms of the receiver operating characteristic (ROC) curves, the performances of the six SSGCN models from high to low are, respectively, models (&lt;em&gt;e&lt;/em&gt;) (&lt;em&gt;c&lt;/em&gt;), (&lt;em&gt;d&lt;/em&gt;), (&lt;em&gt;a&lt;/em&gt;), (&lt;em&gt;f&lt;/em&gt;) and (&lt;em&gt;b&lt;/em&gt;). The area under the ROC curves of the six SSGCN models from high to low are, respectively, (&lt;em&gt;e&lt;/em&gt;) 0.9489, (&lt;em&gt;c&lt;/em&gt;) 0.9457, (&lt;em&gt;d&lt;/em&gt;) 9080, (&lt;em&gt;a&lt;/em&gt;) 0.9039, (&lt;em&gt;f&lt;/em&gt;) 0.8717 and (&lt;em&gt;b&lt;/em&gt;) 0.8453. The polymetallic prospecting targets predicted by the six SSGCN models occupy, respectively, 22.43 %, 8.12 %, 12.93 %, 7.99 %, 7.60 %, 24.16 % of the study area; and correctly classified known polymetallic deposits are, respectively, 88 %, 71 %, 88 %, 82 %, 88 % and 88 %. These results show that the SSGCN model performs best in predicting polymetallic prospecting targets when the cont","PeriodicalId":19644,"journal":{"name":"Ore Geology Reviews","volume":"173 ","pages":"Article 106260"},"PeriodicalIF":3.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fluorescent sphalerite rich in tungsten, copper, gallium, silver, and other elements from the Cordilleran-style, polymetallic veins of Philipsburg, Montana 蒙大拿州菲利普斯堡科迪勒拉山风格多金属矿脉中富含钨、铜、镓、银和其他元素的荧光闪锌矿
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106267
Celine M.E. Beaucamp , Christopher H. Gammons , Jay M. Thompson , Heather A. Lowers
Sphalerite from the central, high-sulfidation zone (enargite-stable) of the Philipsburg polymetallic mining district, southwest Montana, displays unusually bright fluorescence (red, orange, yellow, blue, purple, green) under longwave UV light (365 nm). LA-ICP-MS analysis reveals the fluorescent sphalerite has very low Fe (average < 100 ppm) and variable content of other trace elements that correlate to luminescence color banding. Mean/maximum content (in ppm) in fluorescent sphalerite for selected elements are 5.7/7900 Ag, 107/11800 As, 1400/4730 Cd, 917/30400 Cu, 381/5000 Ga, 32/696 Ge, 119/2130 In, 230/8190 Mn, 43/3000 Pb, 16/1700 Sb, and 89/1980 W. This study is the first to document elevated tungsten content (>10 ppm) in sphalerite. Copper is closely correlated with Ga, consistent with the coupled substitution: Cu+ + Ga3+ = 2Zn2+. Similar coupled substitution reactions can be written for Ag+, In3+, As3+, Sb3+, Bi3+, and Ge4+. However, the brightest red fluorescent bands are most closely related to the unexpected presence of W. Sphalerite with high Cu and Ga but lacking W fluoresces yellow and shows a single Raman peak at 349 cm−1 corresponding to pure sphalerite. In contrast, red-fluorescent sphalerite shows the presence of a second peak at 427 cm−1 that increases in intensity with increased W content. We propose that tungsten enters the sphalerite lattice as W6+ via a substitution such as W6+ + 4Cu+ = 5Zn2+ and that this substitution creates lattice strain that results in the anomalous fluorescence and Raman signals. Sphalerite bands with low concentrations of Cu and Ga fluoresce blue or green. Vivid blue fluorescence is displayed by sphalerite with high Cd (>1000 ppm) but low concentrations of all other trace elements. Sphalerite from the low-sulfidation peripheral mines of the Philipsburg district contains high Fe (>10,000 ppm) and does not fluoresce. Nonetheless, this sphalerite is also highly enriched in trace metals, including Ag (mean 2480/max 8660 ppm), Cu (1610/3440), Mn (7020/8100), and Sb (1960/6390). The results of this study underscore the importance of including tungsten in the list of analytes in future studies of trace elements in sphalerite. In addition, a hand-held UV lamp may be a rapid and cost-effective method to screen sphalerite of variable composition in outcrop or drill core. It may be a useful exploration tool to vector towards a high-sulfidation zone of a zoned porphyry or epithermal deposit, when it is present.
蒙大拿州西南部菲利普斯堡多金属矿区中部高硫化区(enargite-stable)的闪锌矿在长波紫外光(365 纳米)下显示出异常明亮的荧光(红、橙、黄、蓝、紫、绿)。LA-ICP-MS 分析显示,荧光闪锌矿的铁含量非常低(平均为 100 ppm),其他微量元素的含量也不尽相同,这与荧光色带相关。荧光闪锌矿中某些元素的平均/最大含量(ppm)分别为:5.7/7900 Ag、107/11800 As、1400/4730 Cd、917/30400 Cu、381/5000 Ga、32/696 Ge、119/2130 In、230/8190 Mn、43/3000 Pb、16/1700 Sb 和 89/1980 W。铜与镓密切相关,与耦合置换相一致:Cu+ + Ga3+ = 2Zn2+。Ag+、In3+、As3+、Sb3+、Bi3+ 和 Ge4+ 也可以发生类似的耦合置换反应。然而,最明亮的红色荧光带与 W 的意外存在关系最为密切。含有大量铜和镓但缺乏 W 的闪锌矿发出黄色荧光,并在 349 cm-1 处显示出与纯闪锌矿相对应的单拉曼峰。与此相反,红色荧光闪锌矿在 427 cm-1 处显示出第二个峰值,该峰值的强度随着钨含量的增加而增加。我们认为,钨是通过 W6+ + 4Cu+ = 5Zn2+ 等置换作用以 W6+ 的形式进入闪锌矿晶格的,这种置换作用产生了晶格应变,从而导致异常荧光和拉曼信号。含低浓度铜和镓的闪锌矿带发出蓝色或绿色荧光。镉含量高(1000 ppm)但所有其他微量元素含量低的闪锌矿会发出鲜艳的蓝色荧光。来自菲利普斯堡地区低硫化周边矿山的闪锌矿含有较高的铁(>10,000 ppm),不会发出荧光。尽管如此,这种闪锌矿的微量金属含量也很高,包括银(平均 2480/最高 8660 ppm)、铜(1610/3440)、锰(7020/8100)和锑(1960/6390)。这项研究的结果强调了在今后的闪锌矿痕量元素研究中将钨纳入分析物清单的重要性。此外,手持式紫外灯可能是筛选露头或钻芯中不同成分闪锌矿的一种快速、经济有效的方法。如果存在带状斑岩或热液矿床的高硫化区,它可能是一种有用的勘探工具。
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引用次数: 0
Age and petrogenesis of the Madi intrusion in the Huashi area, northern margin of the North China Craton: Implications for magma evolution and Nb–Ta mineralization 华北克拉通北缘花石地区马迭侵入体的年龄和岩石成因:对岩浆演化和铌钽成矿的影响
IF 3.2 2区 地球科学 Q1 GEOLOGY Pub Date : 2024-10-01 DOI: 10.1016/j.oregeorev.2024.106261
ChenYu Liu , GongZheng Chen , ChenChun Zhang , JinFang Wang , Guang Wu , YingJie Li , KangShuo Li , ZeQian Lu , YuTong Song
Although the mineralization of rare earth elements (REEs) and rare metals is intimately associated with the extreme fractionation of granitic magmas, the metallogenic intrusions of many granite-hosted Nb–Ta deposits have undergone fluid–melt interaction. Nevertheless, the precise mechanisms by which fluid–melt interaction influences mineralization remain poorly understood. The present investigation examines the issues of the fluid–melt interaction in highly fractionated granites with Nb–Ta mineralization, utilizing data from the newfound Huashi deposit in the northern margin of the North China Craton (NNCC). The Huashi Nb–Ta–Rb–Li deposit hosted in the Madi intrusion consists of two lithologies that have evolved continuously, namely medium–fine grained granite (MGG) in the lower section and alkali-feldspar granite (AG) at the top. The ages of the MGG and AG were determined using LA–ICP–MS columbite U–Pb dating, yielding values of 182.9 ± 1.7 Ma and 184.7 ± 1.3 Ma, respectively. The Madi intrusion has high SiO2, Al2O3, and total alkali contents, along with low CaO, MgO, MnO, and TFe2O3 contents and high Al2O3 / (CaO + Na2O + K2O) (A/CNK) values, classifying it as highly peraluminous granite with a high-K calc-alkaline affinity. Additionally, the intrusion also exhibits enrichment in Rb, U, Th, and Nb alongside significant depletion in Sr, Ba, Ti, Eu, and P, with a noticeable tetrad effect of REEs. The investigation of mica and feldspar minerals in the Madi intrusion using electron probe microanalysis (EPMA) indicates that the mica is mainly zinnwaldite, while the plagioclase belongs to albite. In summary, the Madi intrusion exhibits a highly I-type fractionated granite affinity. The extreme fractionation, intense fluid–melt interaction, and hydrothermal alteration of the intrusion contribute to the formation of the Huashi deposit.
尽管稀土元素(REEs)和稀有金属的成矿与花岗岩岩浆的极端分馏密切相关,但许多花岗岩型铌钽矿床的成矿侵入体都经历了流体-熔体相互作用。然而,人们对流体-熔体相互作用影响成矿作用的确切机制仍然知之甚少。本研究利用华北克拉通(NNCC)北缘新发现的花石矿床的数据,研究了具有铌钽矿化的高分馏花岗岩中的流体-熔体相互作用问题。华石铌-钽-铷-锂矿床赋存于马迭尔侵入体中,由两种连续演化的岩性组成,即下部的中细粒花岗岩(MGG)和顶部的碱长花岗岩(AG)。采用 LA-ICP-MS 铌铁矿 U-Pb 测定法测定了中细粒花岗岩和 AG 的年龄,结果分别为 182.9 ± 1.7 Ma 和 184.7 ± 1.3 Ma。马迪侵入体的SiO2、Al2O3和总碱含量较高,而CaO、MgO、MnO和TFe2O3含量较低,Al2O3/(CaO + Na2O + K2O)(A/CNK)值较高,因此被归类为具有高K钙碱亲和性的高铝花岗岩。此外,该侵入体还显示出 Rb、U、Th 和 Nb 的富集,同时 Sr、Ba、Ti、Eu 和 P 的显著贫化,具有明显的 REEs 四元效应。利用电子探针显微分析法(EPMA)对马迪侵入体中的云母和长石矿物进行的研究表明,云母主要是黝帘石,而斜长石属于白云母。总之,马迪侵入体表现出高度的I型分馏花岗岩亲和性。该侵入体的极端分馏、强烈的流体-熔体相互作用以及热液蚀变作用促成了花石矿床的形成。
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Ore Geology Reviews
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