TY - JOUR
T1 - Influence of catalyst and solvent on the hydrothermal liquefaction of woody biomass
AU - Zhou, Xinxing
AU - Zhao, Jun
AU - Chen, Meizhu
AU - Zhao, Guangyuan
AU - Wu, Shaopeng
N1 - Funding Information:
This work was funded by the National Natural Science Foundation of China (Nos. 52008235 and 52178437 ). Thanks for the support from Hong Kong Environment and Conservation Fund (No. ECF 2020-46 ), HKBU (No. RC-SGT2/19-20/SCI/009 ).
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/2
Y1 - 2022/2
N2 - Hydrothermal liquefaction of woody biomass with catalysts was commonly applied in bio-energy research, but the effects of catalyst and solvent on yield and properties of bio-energy are not clear. In this work, the influences of catalyst and solvent on bio-energy production were studied, during which four solvents and three catalysts were used, and the liquefaction parameters were optimized by experimental and Machine learning (ML) method. Results show that the maximum yields of bio-oil and biochar are 65.0% and 32.0%, respectively, and the caloric values of bio-oil and biochar are 31.2 MJ/kg and 26.5 MJ/kg, respectively. Alkaline catalysts and 1,4-butanediol-triethanolamine mix solvent can benefit the bio-energy generation. In addition, a Random Forest (RF) was developed to forecast the yields, and the method performed well with experimental results.
AB - Hydrothermal liquefaction of woody biomass with catalysts was commonly applied in bio-energy research, but the effects of catalyst and solvent on yield and properties of bio-energy are not clear. In this work, the influences of catalyst and solvent on bio-energy production were studied, during which four solvents and three catalysts were used, and the liquefaction parameters were optimized by experimental and Machine learning (ML) method. Results show that the maximum yields of bio-oil and biochar are 65.0% and 32.0%, respectively, and the caloric values of bio-oil and biochar are 31.2 MJ/kg and 26.5 MJ/kg, respectively. Alkaline catalysts and 1,4-butanediol-triethanolamine mix solvent can benefit the bio-energy generation. In addition, a Random Forest (RF) was developed to forecast the yields, and the method performed well with experimental results.
KW - Bio-energy
KW - Catalyst
KW - Hydrothermal liquefaction mechanism
KW - Machine learning
KW - Woody biomass
UR - http://www.scopus.com/inward/record.url?scp=85119895593&partnerID=8YFLogxK
U2 - 10.1016/j.biortech.2021.126354
DO - 10.1016/j.biortech.2021.126354
M3 - Journal article
C2 - 34798249
AN - SCOPUS:85119895593
SN - 0960-8524
VL - 346
JO - Bioresource Technology
JF - Bioresource Technology
M1 - 126354
ER -
