Ziyu Wang, Jiele Xu, Jay J. Cheng


To deeply understand the factors that affect the conversion of lignocellulosic biomass to fermentable sugars, experimental results should be bridged with process simulations. The objective of this paper is to review published research on modeling of the pretreatment process using leading technologies such as dilute acid, alkaline, and steam explosion pretreatment, as well as the enzymatic hydrolysis process for converting lignocellulose to sugars. The most commonly developed models for the pretreatment are kinetic models with assumptions of a first-order dependence of reaction rate on biomass components and an Arrhenius-type correlation between rate constant and temperature. In view of the heterogeneous nature of the reactions involved in the pretreatment, the uses of severity factor, artificial neural network, and fuzzy inference systems present alternative approaches for predicting the behavior of the systems. Kinetics of the enzymatic hydrolysis of cellulosic biomass has been simulated using various modeling approaches, among which the models developed based on Langmuir-type adsorption mechanism and the modified Michaelis-Menten models that incorporate appropriate rate-limiting factors have the most potential. Factors including substrate reactivity, enzyme activity and accessibility, irreversible binding of enzymes to lignin, and enzyme deactivation at high conversion levels, need to be considered in modeling the hydrolysis process. Future prospects for research should focus on thorough understanding of the interactions between biomass reactants and chemicals/enzymes — the key to developing sophisticated models for the entire conversion process.


Lignocellulose; Modeling; Pretreatment; Enzymatic Hydrolysis; Kinetics

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Welcome to BioResources! This online, peer-reviewed journal is devoted to the science and engineering of biomaterials and chemicals from lignocellulosic sources for new end uses and new capabilities. The editors of BioResources would be very happy to assist you during the process of submitting or reviewing articles. Please note that logging in is required in order to submit or review articles. Martin A. Hubbe, (919) 513-3022,; Lucian A. Lucia, (919) 515-7707, URLs:; ISSN: 1930-2126