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HE Jia-le, GONG Ting-ting, PAN Zhong-xi, DU Gu. Raman Imaging Analysis Method of Fine Minerals in Rock Ore[J]. Rock and Mineral Analysis, 2021, 40(4): 491-503. DOI: 10.15898/j.cnki.11-2131/td.202103080036
Citation: HE Jia-le, GONG Ting-ting, PAN Zhong-xi, DU Gu. Raman Imaging Analysis Method of Fine Minerals in Rock Ore[J]. Rock and Mineral Analysis, 2021, 40(4): 491-503. DOI: 10.15898/j.cnki.11-2131/td.202103080036

Raman Imaging Analysis Method of Fine Minerals in Rock Ore

More Information
  • Received Date: March 07, 2021
  • Revised Date: May 13, 2021
  • Accepted Date: July 01, 2021
  • Published Date: July 27, 2021
  • HIGHLIGHTS
    (1) StreamLineHR was used to identify fine minerals and to systematically analyze their composition and concentrations.
    (2) The effects of experimental conditions, fluorescence interference, and spectral fitting parameters on the Raman mapping results were analyzed.
    (3) The differences among the mapping technique, traditional identification methods, SEM, and other technical methods were compared.
    BACKGROUNDMineral identification is the basis of all types of geological work, and its appraisal level and quality directly affect the depth and degree of research of a study. Conventional identification methods are significantly influenced by experience level, optical microscope resolution, and other factors. It is difficult to accurately identify fine rare minerals and clay minerals that need to be studied. Additionally, most of the technical methods relying on high-precision large-scale instruments have special requirements for sample preparation, which is not conducive to the reuse of the samples. It is also inconvenient to explore and observe specific fine transparent minerals under high multiple reflected lights, such as scanning electron microscopy and electron microprobe.
    OBJECTIVESTo develop a more rapid and accurate method for identifying fine minerals.
    METHODSThe laser Raman high-resolution large-area fast imaging method (StreamLineHR) was applied to the whole-area large-area scanning spectrum of two standard rock slices.
    RESULTSThe transparent minerals were identified as alkali feldspar, plagioclase, quartz, amphibole, biotite, calcite, sphene, apatite, zircon, and epidote. The opaque mineral was identified as magnetite. Some of the minerals were closely associated (e.g., quartz and feldspar as well as sphene and hornblende), and some minerals showed secondary alterations (e.g., feldspar was transformed to calcite). Based on the content statistics, the two thin sections were named fine-grained amphibolite monzonite and fine-grained biotite plagioclase amphibolite.
    CONCLUSIONSExperimental results showed that this method was more accurate than the conventional methods used for the identification of fine minerals with very low content. However, the interference caused by the fluorescence effect, similarity in peak positions of similar minerals (feldspar, amphibole), and shift of the peak position of altered minerals during mineral identification and spectral fitting were solved by combining the optical characteristics under the mineral objective lens when necessary. In addition, the smaller the setting of the surface sweep step size, the more accurate the analysis, and the time cost correspondingly increased. This method realized the rapid identification of fine minerals over a large range, which was convenient, intuitive, and accurate. It compensated for the shortcomings of conventional rock and ore identification and other technical methods and expanded the application scope of Raman spectroscopy in geological studies.

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