Investigation of Component Interactions During the Hydrothermal Process Using a Mixed-Model Cellulose/Hemicellulose/Lignin/Protein and Real Cotton Stalk

Shengjun Guo, Jiachen Zuo, Xiao Yang, Hui Wang, Lihua Cheng and Libo Zhang ()
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Shengjun Guo: Guangdong Provincial Engineering & Technology Center for Corrosion and Safety in Petrochemical Industry, School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
Jiachen Zuo: Guangdong Provincial Engineering & Technology Center for Corrosion and Safety in Petrochemical Industry, School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
Xiao Yang: State Key Laboratory of Heavy Oil Processing, College of Engineering, China University of Petroleum-Beijing at Karamay, Karamay 834000, China
Hui Wang: Guangdong Provincial Engineering & Technology Center for Corrosion and Safety in Petrochemical Industry, School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
Lihua Cheng: Guangdong Provincial Engineering & Technology Center for Corrosion and Safety in Petrochemical Industry, School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
Libo Zhang: Guangdong Provincial Engineering & Technology Center for Corrosion and Safety in Petrochemical Industry, School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China

Energies, 2025, vol. 18, issue 5, 1-17

Abstract: Converting agricultural and forestry waste into high-value-added bio-oil via hydrothermal liquefaction (HTL) reduces incineration pollution and alleviates fuel oil shortages. Current research focuses on adjusting HTL parameters like temperature, time, catalyst, and pretreatment. Few studies explore raw material composition and its interactions with bio-oil properties, limiting guidance for future multi-material hydrothermal co-liquefaction. In view of the above problems, the lignocellulosic model in this paper used cellulose, hemicellulose, lignin, and protein as raw materials. At a low hydrothermal temperature (220 °C), the yield and properties of hydrothermal bio-oil were used as indicators to explore the influence of the proportional content of different model components on the interaction in the hydrothermal process through its simple binary blending and multivariate blending. Then, compared with the hydrothermal liquefaction process of cotton stalk, the interaction between components in the hydrothermal process of real lignocellulose was explored. The results demonstrated significant interactions among cellulose, lignin, and hemicellulose in cotton stalks. The relative strength of component interactions was ranked by yield (wt.%) and property modulation as follows: cellulose–lignin (C-L, 6.82%, synergistic enhancement) > cellulose–hemicellulose (C-X, 1.83%, inhibitory effect) > hemicellulose–lignin (X-L, 1.32%, non-significant interaction). Glycine supplementation enhanced bio-oil yields, with the most pronounced effect observed in cellulose–glycine (C-G) systems, where hydrothermal bio-oil yield increased from 2.29% to 4.59%. Aqueous-phase bio-oil exhibited superior high heating values (HHVs), particularly in hemicellulose–glycine (X-G) blends, which achieved the maximum HHV of 29.364 MJ/kg among all groups. Meanwhile, the characterization results of hydrothermal bio-oil under different mixing conditions showed that the proportion of model components largely determined the composition and properties of hydrothermal bio-oil, which can be used as a regulation method for the synthesis of directional chemicals. Cellulose–lignin (C-L) interactions demonstrated the strongest synergistic enhancement, reaching maximum efficacy at a 3:1 mass ratio. This study will deepen the understanding of the composition of lignocellulose raw materials in the hydrothermal process, promote the establishment of a hydrothermal product model of lignocellulose, and improve the yield of bio-oil.

Keywords: cotton stalk; hydrothermal liquefaction; binary blending; multivariate blending; interaction; bio-oil (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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