State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China; Key Laboratory of Highway Construction and Maintenance Technology in Loess Region of Ministry of Transport, Shanxi Transportation Technology Research & Development Co., Ltd, Taiyuan 030032, China.
Institute of Bioresource and Agriculture, Department of Biology, Hong Kong Baptist University, Hong Kong SAR, China.
Bioresour Technol. 2022 Feb;346:126354. doi: 10.1016/j.biortech.2021.126354. Epub 2021 Nov 17.
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 caloricvalues 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.
水热液化木质生物质与催化剂通常应用于生物能源研究，但催化剂和溶剂对生物能源的产量和性质的影响尚不清楚。在这项工作中，研究了催化剂和溶剂对生物能源生产的影响，使用了四种溶剂和三种催化剂，并通过实验和机器学习（ML）方法优化了液化参数。结果表明，生物油和生物炭的最大产率分别为 65.0%和 32.0%，生物油和生物炭的热值分别为 31.2 MJ/kg 和 26.5 MJ/kg。碱性催化剂和 1,4-丁二醇-三乙醇胺混合溶剂有利于生物能源的生成。此外，还开发了随机森林（RF）来预测产量，该方法与实验结果吻合良好。
