Parametric Study of Yields and Properties of Corn Stover-Derived Hydrothermal Liquefaction Products by Using Statistical Approaches

Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PCA) and regression modeling to predict AP solution weight, LBO weight and fuel characteristics, and HTL wastewater biodegradability, as well as to improve prediction accuracy for SR and HBO under various operating conditions (temperature: 250–350 °C, residence time: 5–60 min, and the combined solid loading of three batches: 15–45 g). A complementary relationship between SR and AP weights found in PCA enabled the estimation of AP weight based on predicted SR values in a regression analysis. A modified partition coefficient was introduced to link LBO weight with the carbon content of AP and was predicted, enabling accurate LBO yield estimation. Although LBO fuel characteristics could not be modeled reliably, those of SR and HBO were predicted with improved accuracy over prior kinetic models. The concentration of catechol in HTL wastewater (HTL-WW) was also modeled from operating conditions and linked to half-maximal inhibitory concentration (IC50) of R. jostii and A. niger as a biodegradability index. This work demonstrates the feasibility of predicting underrepresented HTL outputs using statistical approaches.