Quantitative Identification of Detrital Minerals by Mineral Characteristic Automatic Analysis System and Error Analysis with Traditional Microscopic Identification

NING Ze; XU Lei; LIN Xuehui; ZHANG Yuanyuan; ZHANG Yong

doi:10.15898/j.ykcs.202310190163

2024 Vol. 43, No. 5

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Article navigation > Rock and Mineral Analysis > 2024 > 43(5): 713-722

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NING Ze, XU Lei, LIN Xuehui, ZHANG Yuanyuan, ZHANG Yong. Quantitative Identification of Detrital Minerals by Mineral Characteristic Automatic Analysis System and Error Analysis with Traditional Microscopic Identification[J]. Rock and Mineral Analysis, 2024, 43(5): 713-722. doi: 10.15898/j.ykcs.202310190163

Citation:

NING Ze, XU Lei, LIN Xuehui, ZHANG Yuanyuan, ZHANG Yong. Quantitative Identification of Detrital Minerals by Mineral Characteristic Automatic Analysis System and Error Analysis with Traditional Microscopic Identification[J]. Rock and Mineral Analysis, 2024, 43(5): 713-722. doi: 10.15898/j.ykcs.202310190163

Quantitative Identification of Detrital Minerals by Mineral Characteristic Automatic Analysis System and Error Analysis with Traditional Microscopic Identification

1.
Qingdao Institute of Marine Geology, China Geological Survey, Qingdao 266237, China
2.
Marine Geological Experimental Testing Center, Ministry of Natural Resources, Qingdao 266237, China

More Information

Corresponding author: XU Lei, 2279487719@qq.com

Received Date: 19 October 2023

Revised Date: 23 August 2024

Accepted Date: 02 September 2024

Publish Date: 30 September 2024

Abstract

Abstract

The analysis of detrital minerals is widely used in the study of sediment sources and material diffusion, and is of great significance in analyzing sedimentary dynamic environment and oceanic dynamic characteristics. However, for a long time, the acquisition of detrital mineral data has relied mainly on optical microscopes as tools and manual identification, which is labor-intensive and inefficient. In order to obtain scientific and effective mineral identification data in a timely fashion, a thermal field emission scanning electron microscopy with energy dispersive spectroscopy attached and an automated mineral identification and characterization system (AMICS) were used. For the first sample, 25 mineral species were identified by the AMICS system and 25 mineral species were identified by artificial identification with stereomicroscope and polarizing microscope. For the second sample, 26 mineral species were identified by the AMICS system, and 27 mineral species were identified by artificial identification. The two methods identified similar types of detrital minerals, and the absolute error of each mineral content was less than 5%. The AMICS system can be used to identify oxides (limonite, chromite, etc.), phosphates (apatite, etc.), sulfates (barite, etc.), sulfides (pyrite, etc.), carbonates (calcite, dolomite, etc.), and some silicates (zircon, titanite, olivine, quartz, potassium feldspar, sodium feldspar, garnet group, etc.) accurately but it is difficult to accurately identify polymorphic and isomorphic detrital minerals based solely on mineral chemical composition. The problem of layered silicate minerals easily falling off layer by layer during sample preparation needs to be solved.

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References

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