Classification and Discrimination of Minerals Using Laser Induced Breakdown Spectroscopy and Raman Spectroscopy

BI Yunfeng (毕云峰); ZHANG Ying (张莹); YAN Jingwen (闫静文); WU Zhongchen (武中臣); LI Ying (李颖)

doi:10.1088/1009-0630/17/11/06

Plasma Science and Technology > 2015 > 17(11): 923-927. > DOI: 10.1088/1009-0630/17/11/06

BI Yunfeng (毕云峰), ZHANG Ying (张莹), YAN Jingwen (闫静文), WU Zhongchen (武中臣), LI Ying (李颖). Classification and Discrimination of Minerals Using Laser Induced Breakdown Spectroscopy and Raman Spectroscopy[J]. Plasma Science and Technology, 2015, 17(11): 923-927. DOI: 10.1088/1009-0630/17/11/06

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Classification and Discrimination of Minerals Using Laser Induced Breakdown Spectroscopy and Raman Spectroscopy

1School of Mechanicals, Electrical & Information Engineering, Shandong University (Weihai), Weihai 264209, China 2Optics and Optoelectronics Laboratory, Ocean University of China, Qingdao 266100, China 3School of Space Science and Physics, Shandong University (Weihai), Weihai 264209, China

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Received Date: March 22, 2015

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Abstract

Abstract

he classification and discrimination of minerals are important in geological re?search. The distribution of rocks and minerals may be inferred based on their identi?cation, which is helpful for the investigation of some geological and environmental evolution problems, either on the earth or on other planets. LIBS and Raman spectra techniques have shown great advantages in simultaneous multi-component, in-situ, and non-destructive detection and they play an important role in rock composition analysis. In this presentation, six kinds of minerals (Gyp?sum, Spodumene, Barite, Haematite, Moonstone, and Labradorite) were detected by first using LIBS and Raman systems, and then several other methods (PCA, PLS-DA, ANN, and SVM) were used to evaluate the LIBS, Raman, and the fused LIBS/Raman data, respectively. The results indicate the superiority of the fused LIBS/Raman data in mineral classi?cation, which stems from their complementary analysis abilities when studying element composition and structural features.
- mineral classification,
- LIBS,
- Raman spectra,
- multivariate analysis

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References

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