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梁述廷, 刘玉纯, 刘瑱, 林庆文, 刘志伟. X射线荧光光谱微区分析在铜矿物类质同象鉴定中的应用[J]. 岩矿测试, 2015, 34(2): 201-206. DOI: 10.15898/j.cnki.11-2131/td.2015.02.008
引用本文: 梁述廷, 刘玉纯, 刘瑱, 林庆文, 刘志伟. X射线荧光光谱微区分析在铜矿物类质同象鉴定中的应用[J]. 岩矿测试, 2015, 34(2): 201-206. DOI: 10.15898/j.cnki.11-2131/td.2015.02.008
Shu-ting LIANG, Yu-chun LIU, Zhen LIU, Qing-wen LIN, Zhi-wei LIU. Application of In-situ Micro-XRF Spectrometry in the Identification of Copper Minerals[J]. Rock and Mineral Analysis, 2015, 34(2): 201-206. DOI: 10.15898/j.cnki.11-2131/td.2015.02.008
Citation: Shu-ting LIANG, Yu-chun LIU, Zhen LIU, Qing-wen LIN, Zhi-wei LIU. Application of In-situ Micro-XRF Spectrometry in the Identification of Copper Minerals[J]. Rock and Mineral Analysis, 2015, 34(2): 201-206. DOI: 10.15898/j.cnki.11-2131/td.2015.02.008

X射线荧光光谱微区分析在铜矿物类质同象鉴定中的应用

Application of In-situ Micro-XRF Spectrometry in the Identification of Copper Minerals

  • 摘要: 铜矿物种类繁多, 赋存状态各异, 成分复杂, 由于共生矿物和伴生矿物的存在, 增加了传统岩矿鉴定工作的难度。特别是铜矿物间存在的类质同象现象(黝铜矿和砷黝铜矿)和铜矿物与其他矿物间(磁黄铁矿和方黄铜矿)存在镜下光学特征相似的现象, 应用偏光或反光显微镜难以给铜矿物准确定名。本文应用具有微区分析功能的X射线荧光光谱仪扫描铜矿物标本谱图, 通过选择测量条件、测量方式和干扰校正模型(谱线重叠和基体效应)建立了类质同象物相的鉴定方法。该方法具有较高的精密度和准确度, 对黄铜矿标本进行12次测定, S、Fe、Cu的相对标准偏差(RSD)分别为0.74%、0.86%、0.18%;对铜矿物标准样品进行单次测定, 待测元素的测量结果与推荐值的相对误差均小于6%。该方法可准确甄别出黝铜矿与含银砷黝铜矿、磁黄铁矿与方黄铜矿; 测量效率高, 能够提供主量元素和主要伴生元素的二维或三维图像, 直观地呈现矿物的分布情况, 为铜矿物的准确定名和矿物的综合利用提供了有价值的信息。

     

    Abstract: There are many types of copper minerals with different occurrences and complex compositions. The paragenesis and associated minerals make it difficult to traditionally identify the rock and mineral. In particular, the isomorphism of tetrahedrite and tennantite and the similar optical characteristics of copper minerals with pyrrhotine and cubanite make the identification of copper mineral difficult by Polarization Microscope or Reflection Microscope. In this paper, an account of how the copper mineral was scanned by X-ray Fluorescence Spectrometry (XRF) with microanalysis is given. By selecting the measurement conditions, measurement modes, and interference correction model (spectral overlap and matrix effects), the identification method was established. This method has excellent precision and accuracy. The relative standard deviations (RSD) of S, Fe and Cu are 0.74%, 0.86% and 0.18%, respectively for 12 repeated analyses of chalcopyrite. Single analysis of copper mineral standard yields the RSD less than 6%. The proposed method can identify tetrahedrite from Ag-As tetrahedrite, and also pyrrhotite and cubanite. This method is effective and can provide two-dimensional or three-dimensional images of the major elements and associated elements, which directly show the distribution of minerals and provides valuable information for accurately naming copper minerals and the comprehensive utilization of minerals.

     

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