The key for sodium-rich coal utilization in entrained flow gasifier: The role of sodium on slag viscosity-temperature behavior at high temperatures
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DOI: 10.1016/j.apenergy.2017.10.020
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Cited by:
- Xiongchao Lin & Wenshuai Xi & Jinze Dai & Caihong Wang & Yonggang Wang, 2020. "Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes," Energies, MDPI, vol. 13(19), pages 1-18, October.
- Liu, Yingzu & He, Yong & Wang, Zhihua & Xia, Jun & Wan, Kaidi & Whiddon, Ronald & Cen, Kefa, 2018. "Characteristics of alkali species release from a burning coal/biomass blend," Applied Energy, Elsevier, vol. 215(C), pages 523-531.
- Yang, Wei & Zhu, Youjian & Cheng, Wei & Sang, Huiying & Xu, Hanshen & Yang, Haiping & Chen, Hanping, 2018. "Effect of minerals and binders on particulate matter emission from biomass pellets combustion," Applied Energy, Elsevier, vol. 215(C), pages 106-115.
- Wang, Kangcheng & Zhang, Jie & Shang, Chao & Huang, Dexian, 2021. "Operation optimization of Shell coal gasification process based on convolutional neural network models," Applied Energy, Elsevier, vol. 292(C).
- Wu, Guixuan & Seebold, Sören & Yazhenskikh, Elena & Tanner, Joanne & Hack, Klaus & Müller, Michael, 2019. "Slag mobility in entrained flow gasifiers optimized using a new reliable viscosity model of iron oxide-containing multicomponent melts," Applied Energy, Elsevier, vol. 236(C), pages 837-849.
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Keywords
Entrained flow gasification; Sodium-rich coal; Viscosity-temperature behavior; Network structure; Crystallization tendency;All these keywords.
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