 Hydrothermal liquefaction of biomass model components for product yield prediction and reaction pathways explorationJie Yang, He, Quan (Sophia), Haibo Niu, Kenneth Corscadden and Tess Astatkie Applied Energy, 2018, vol. 228, issue C, 1618-1628 Abstract: Hydrothermal liquefaction (HTL) is a promising technology for crude bio-oil production from a variety of biomass, however, there is a lack of prediction models for the yield of products and the reaction pathways is not well understood. Prediction models for biocrude yield and solid residue (SR) yield were developed by using a mixture design of five model components, including xylan (hemicellulose), crystalline cellulose, alkaline lignin, soya protein and soybean oil in this study. The model predictability was verified by using actual feedstock as well as a mixture of model components based on the chemical composition of the feedstock of concern. The biocrude yield, solid residue yield and quantitative chemical yields obtained from bio-oil were used to explore the reaction pathways as well as possibly existing synergistic and/or antagonistic interactions between two studied model components. It was found that both hemicellulose and lipid (H∗Lip) and cellulose and lipid (C∗Lip) interactions had synergistic effect on the biocrude yield, while SR yield was antagonistically decreased by the cellulose and lignin (C∗Lig) interaction. Maillard reactions between protein and carbohydrates and amide formation between protein and lipid were observed. The carbohydrates and lipid interactions had effects on the acid yield (in H∗Lip), hydrocarbon yield and ketone yield (in C∗Lip), but lignin and lipid (in Lig∗Lip) behaved independently in the HTL processes. The findings of this research can be used to assess the potential of various kinds of biomass, provide guidance for using mixed biomass (co-liquefaction) and tailor the chemical composition of feedstock for a desirable product distribution in HTL processes. Keywords: Hydrothermal liquefaction; Quantities prediction models; Bio-oil; Reaction pathway; Lignocellulosic model compounds; Mixture design (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:228:y:2018:i:c:p:1618-1628 Ordering information: This journal article can be ordered from DOI: 10.1016/j.apenergy.2018.06.142 Access Statistics for this article Applied Energy is currently edited by J. Yan More articles in Applied Energy from Elsevier |
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