Components Interaction of Cotton Stalk under Low-Temperature Hydrothermal Conversion: A Bio-Oil Pyrolysis Behavior Perspective Analysis

The conversion of agricultural and forestry waste biomass materials into bio-oil by mild hydro-thermal technology has a positive effect on extending the agricultural industry chain and alleviating the world energy crisis. The interaction investigation of biomass components during bio-oil formation can be significant for the efficient conversion of lignocellulose when different raw materials are fed together. In this paper, a bio-oil pyrolysis behavior (thermogravimetric analysis, TG) perspective component interaction investigation of cotton stalks under low-temperature hydro-thermal conversion (220 °C) was studied. Cellulose, hemi-cellulose, lignin, and protein were used as lignocellulose model components, by their simple binary blending and multi-variate blending and combined with thermo-gravimetric analysis and gas chromatography-mass spectrometry (GC-MS) characterization and analysis. The interaction of different model components and real biomass raw material components in the hydro-thermal process was explored. Results showed that the components of hydro-thermal bio-oil from cotton stalks were highly correlated with the interactions between cellulose, hemi-cellulose, lignin, and protein. During the hydro-thermal process, cellulose and hemi-cellulose inhibit each other, which reduces the content of ketones, aldehydes, ethers, and alcohols in bio-oil. Interaction between cellulose and lignin was obvious, which promotes the formation of oligomers, such as ketones, aldehydes, esters, phenols, and aliphatic, while inhibiting the production of aromatic and multi-hybrid compounds. Otherwise, there was no obvious interaction effect between hemi-cellulose and lignin or between lignin and protein. This research will guide the industrialization of lignocellulose, especially the possible co-feed hydro-thermal conversion technology.Keywords:bio-oil;cotton stalk;hydro-thermal liquefaction;interaction;multi-variate blending