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Spectral characterization of the key parameters and elements in coal using terahertz spectroscopy

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  • Zhan, Honglei
  • Zhao, Kun
  • Xiao, Lizhi

Abstract

The augmenting necessity of energy saving and environmental protection has led to the increasing technical requirements about on-line monitoring of key parameters and elements in coal. In this study, terahertz spectroscopy combined with PCA (principal components analysis) was employed to analyze nine kinds of coal materials. Due to the strong absorption of the organics with the relatively high C/H ratio, such as aromatic compounds, coals with lower hydrogen content show higher absorption effects in terahertz range. Based on PC1 score calculated by PCA, the anthracite and bituminous coal can be clearly classified, and the clean as well as meagre coals were also distinguished by opposite trends. All the critical points in PCA system are in agreement with those (volatile matter and ash, respectively) classified in international standard of coal classification. In addition, significant elements, including carbon, hydrogen, nitrogen and sulfur, can be directly characterized using PC1 score with linear and non-linear models. This research indicates that the terahertz spectral analysis of key parameters and elements of coal is a promising tool for improving the detection method and advancing the technical innovation in coal processing industry.

Suggested Citation

  • Zhan, Honglei & Zhao, Kun & Xiao, Lizhi, 2015. "Spectral characterization of the key parameters and elements in coal using terahertz spectroscopy," Energy, Elsevier, vol. 93(P1), pages 1140-1145.
  • Handle: RePEc:eee:energy:v:93:y:2015:i:p1:p:1140-1145
    DOI: 10.1016/j.energy.2015.09.116
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    References listed on IDEAS

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    Cited by:

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    2. Zhan, Honglei & Chen, Mengxi & Zhao, Kun & Li, Yizhang & Miao, Xinyang & Ye, Haimu & Ma, Yue & Hao, Shijie & Li, Hongfang & Yue, Wenzheng, 2018. "The mechanism of the terahertz spectroscopy for oil shale detection," Energy, Elsevier, vol. 161(C), pages 46-51.
    3. Zhu, Hongqing & Liao, Qi & Qu, Baolin & Hu, Lintao & Wang, Haoran & Gao, Rongxiang & Zhang, Yilong, 2023. "Relationship between the main functional groups and complex permittivity in pre-oxidised lignite at terahertz frequencies based on grey correlation analysis," Energy, Elsevier, vol. 278(C).
    4. Zhan, Honglei & Wang, Yan & Chen, Mengxi & Chen, Ru & Zhao, Kun & Yue, Wenzheng, 2020. "An optical mechanism for detecting the whole pyrolysis process of oil shale," Energy, Elsevier, vol. 190(C).

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