水热液化
液化
生物炭
催化作用
生物量(生态学)
溶剂
三乙醇胺
化学
制浆造纸工业
热液循环
产量(工程)
生物能源
化学工程
环境科学
废物管理
材料科学
生物燃料
核化学
有机化学
热解
农学
复合材料
分析化学(期刊)
工程类
生物
作者
Xinxing Zhou,Jun Zhao,Meizhu Chen,Guangyuan Zhao,Shaopeng Wu
标识
DOI:10.1016/j.biortech.2021.126354
摘要
Abstract 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 31.2MJ/kg and 26.5MJ/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.
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