Influence of catalyst and solvent on the hydrothermal liquefaction of woody biomass. (February 2022)

• Record Type: Journal Article
• Authors: Zhou, Xinxing; Zhao, Jun; Chen, Meizhu; Zhao, Guangyuan; Wu, Shaopeng
• Is Part Of: Bioresource technology. Volume 346(2022)
• Publication Date: 2022-02
• Subjects: Woody biomass -- Bio-energy -- Hydrothermal liquefaction mechanism -- Catalyst -- Machine learning; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2021.126354
• Languages: English
• ISSNs: 0960-8524

Abstract

Graphical abstract: Highlights: The effects of solvents and catalysts on the bio-energy were investigated. Machine learning was developed to predict the yields of bio-energy. The influences of reaction conditions on chemical properties of bio-energy were studied. Machine learning-based optimization of preparation parameter was proposed. 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 31.2 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.