Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning
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DOI: 10.1016/j.apenergy.2020.115166
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- Mau, Vivian & Gross, Amit, 2018. "Energy conversion and gas emissions from production and combustion of poultry-litter-derived hydrochar and biochar," Applied Energy, Elsevier, vol. 213(C), pages 510-519.
- Ciuta, Simona & Patuzzi, Francesco & Baratieri, Marco & Castaldi, Marco J., 2018. "Enthalpy changes during pyrolysis of biomass: Interpretation of intraparticle gas sampling," Applied Energy, Elsevier, vol. 228(C), pages 1985-1993.
- Ismail, Tamer M. & Yoshikawa, Kunio & Sherif, Hisham & Abd El-Salam, M., 2019. "Hydrothermal treatment of municipal solid waste into coal in a commercial Plant: Numerical assessment of process parameters," Applied Energy, Elsevier, vol. 250(C), pages 653-664.
- Zhao, Peitao & Chen, Hongfang & Ge, Shifu & Yoshikawa, Kunio, 2013. "Effect of the hydrothermal pretreatment for the reduction of NO emission from sewage sludge combustion," Applied Energy, Elsevier, vol. 111(C), pages 199-205.
- Zhao, Peitao & Shen, Yafei & Ge, Shifu & Chen, Zhenqian & Yoshikawa, Kunio, 2014. "Clean solid biofuel production from high moisture content waste biomass employing hydrothermal treatment," Applied Energy, Elsevier, vol. 131(C), pages 345-367.
- Salcedo-Sanz, S. & Cornejo-Bueno, L. & Prieto, L. & Paredes, D. & García-Herrera, R., 2018. "Feature selection in machine learning prediction systems for renewable energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 728-741.
- Yu, Yang & Lei, Zhongfang & Yang, Xi & Yang, Xiaojing & Huang, Weiwei & Shimizu, Kazuya & Zhang, Zhenya, 2018. "Hydrothermal carbonization of anaerobic granular sludge: Effect of process temperature on nutrients availability and energy gain from produced hydrochar," Applied Energy, Elsevier, vol. 229(C), pages 88-95.
- Li, Liang & Flora, Joseph R.V. & Berge, Nicole D., 2020. "Predictions of energy recovery from hydrochar generated from the hydrothermal carbonization of organic wastes," Renewable Energy, Elsevier, vol. 145(C), pages 1883-1889.
- Tripathi, Manoj & Sahu, J.N. & Ganesan, P., 2016. "Effect of process parameters on production of biochar from biomass waste through pyrolysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 467-481.
- Huang, Yu-Fong & Cheng, Pei-Hsin & Chiueh, Pei-Te & Lo, Shang-Lien, 2017. "Leucaena biochar produced by microwave torrefaction: Fuel properties and energy efficiency," Applied Energy, Elsevier, vol. 204(C), pages 1018-1025.
- Tian, Hailin & Li, Jie & Yan, Miao & Tong, Yen Wah & Wang, Chi-Hwa & Wang, Xiaonan, 2019. "Organic waste to biohydrogen: A critical review from technological development and environmental impact analysis perspective," Applied Energy, Elsevier, vol. 256(C).
- Liu, Zhengang & Quek, Augustine & Balasubramanian, R., 2014. "Preparation and characterization of fuel pellets from woody biomass, agro-residues and their corresponding hydrochars," Applied Energy, Elsevier, vol. 113(C), pages 1315-1322.
- Li, Hui & Liu, Xinhua & Legros, Robert & Bi, Xiaotao T. & Jim Lim, C. & Sokhansanj, Shahab, 2012. "Pelletization of torrefied sawdust and properties of torrefied pellets," Applied Energy, Elsevier, vol. 93(C), pages 680-685.
- Chiang, Kung-Yuh & Chien, Kuang-Li & Lu, Cheng-Han, 2012. "Characterization and comparison of biomass produced from various sources: Suggestions for selection of pretreatment technologies in biomass-to-energy," Applied Energy, Elsevier, vol. 100(C), pages 164-171.
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- Li, Chunxing & Wang, Yu & Xie, Shengyu & Wang, Ruming & Sheng, Hu & Yang, Hongmin & Yuan, Zengwei, 2024. "Synergistic treatment of sewage sludge and food waste digestate residues for efficient energy recovery and biochar preparation by hydrothermal pretreatment, anaerobic digestion, and pyrolysis," Applied Energy, Elsevier, vol. 364(C).
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- Gabriella Gonnella & Giulia Ischia & Luca Fambri & Luca Fiori, 2022. "Thermal Analysis and Kinetic Modeling of Pyrolysis and Oxidation of Hydrochars," Energies, MDPI, vol. 15(3), pages 1-21, January.
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Keywords
Biochar; Waste to energy; Pyrolysis; Hydrothermal carbonization; Machine learning; Multi-task prediction;All these keywords.
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