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A study of the relationships between coal structures and combustion characteristics: The insights from micro-Raman spectroscopy based on 32 kinds of Chinese coals
- Xu, Jun, Tang, Hao, Su, Sheng, Liu, Jiawei, Xu, Kai, Qian, Kun, Wang, Yi, Zhou, Yingbiao, Hu, Song, Zhang, Anchao, Xiang, Jun
- Applied energy 2018 v.212 pp. 46-56
- Raman spectroscopy, aromatic compounds, coal, combustion, crosslinking, temperature
- Structures and combustion characteristics of 32 kinds of Chinese coals were studied by Micro-Raman spectroscopy and thermal gravimetric analyzer. Changes in coal structures with coalification were investigated by detailed curve-fitting the Raman spectrum with ten Gaussian bands. The relationships between the Raman spectral parameters and coal combustion characteristics were set up and evaluated. The results indicate that the loss of aromatic substituents or aliphatic structures can be responsible for the decrease of Vdaf for low rank coals (volatiles content in dry ash-free basis (Vdaf) > 25%), while the rapid growth of aromatic rings along with the increase of cross-linking density of coals mainly occurs under coalification for relative high rank coal (Vdaf > 25%). Besides, C O structures in coal increase monotonously with the increase of Vdaf. The condensation of aromatic rings, loss of C O structures and reduction of “impurity” structures among large aromatic rings all can increase the coal combustion characteristic temperatures. Reasonable correlations between the coal combustion characteristic temperatures: Ti, Tm, Tb and Raman spectral parameters: A(GR+VL+VR)/AD, AGL/ATotal, AS/AD, AD/ATotal have been found respectively, and the relationships are all better than that between Ti, Tm, Tb and Vdaf. Particularly, the Raman spectral parameter AD/ATotal is a combination of above key parameters and related to the coal ignition temperature best with the R-square higher than 0.9. AD/ATotal can act as a good indicator for coal combustion characteristics. This study directly demonstrates that Raman spectroscopy can play a probe not only for coal ranks/structures but also coal combustion characteristics and it can provide a new approach to rapidly predict the coal properties.