284017 Optimization of Biochemical Conversion Process of Lignocellulosic Biomass to Sugars by Integrating the Kinetic Models

Wednesday, October 31, 2012: 5:15 PM
323 (Convention Center )
Vasanth Natarajan, Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, Singapore and Iftekar A. Karimi, Dept of Chemical & Biomolecular Engineering, National University of Singapore, Singapore, Singapore

Over the years, interest in new ways of producing biofuels is increasing rapidly in response to rising prices of gasoline, depletion of fossil fuels and the non-renewable nature of crude oil. Bioethanol, the first generation biofuel is a highly established renewable fuel today which comes from sugar or grain (starch). The production of second generation biofuel from cheaper, abundant lignocellulosic feedstocks (LCF) emerged as a potential alternative feedstock to highly competitive food based raw materials. For lignocellulosic biofuels to become a reality, research in the development of cost and energy effective biochemical conversion of biomass to sugars are highly needed. With a lot of improvements in the experimental studies of various pretreatment, saccharification and fermentation processes, a significant improvement from a modeling and optimization perspective is required.           

In the literature, studies have been done on kinetic modeling [1], statistical and non-statistical techniques [2, 3] for process design and optimization. Until the present, most of the modeling based works focus on the optimization of size reduction process [4], pretreament process, saccharification and fermentation individually. For predicting the behaviour of the entire conversion system it is essential to integrate existing models for efficient process optimization [5]. In this work, we propose a model based optimization approach for the biochemical conversion of biomass to sugars by considering the overall conversion process. Our major objective of this work is to minimize the amount of energy required for the conversion process by determining the optimal design variables. Here, we integrate the kinetic models of dilute acid pretreatment, enzymatic hydrolysis and fermentation process. Also, we consider the physical (size reduction) and chemical aspects (diffusion models) of the biomass for a more detailed study of the above system. The above problem has been formulated in GAMS including the mass balance equations, kinetic equations, and the equations involved in size reduction and diffusion processes.

Finally, we present the results based on the minimal amount of energy consumed by the entire conversion process of lignocellulosic biomass to sugars. We have considered cornstover as our raw material due to its vast availability of experimental and theoretical data. This study shows the need for sophisticated models that considers the integrated models of the conversion process and also, the physical and chemical aspects of the biomass which is the novelty and the contribution of this work.

 1.            Esteghlalian, A., et al., Modeling and optimization of the dilute-sulfuric-acid pretreatment of corn stover, poplar and switchgrass. Bioresource Technology, 1997. 59(2-3): p. 129-136.

 2.            Ramirez, M.T. and E.S. Fraga, Mathematical Modelling of Feed Pretreatment for Bioethanol Production, 2009. p. 1299-1304.

 3.            Vargas Betancur, G.J. and N. Pereira Jr, Sugar cane bagasse as feedstock for second generation ethanol production. Part I: Diluted acid pretreatment optimization. Electronic Journal of Biotechnology, 2010. 13(3): p. 1-9.

4.            Sayed Ali Hosseini, R.L., Sergei Kucherenko, and Nilay Shah, Multiscale Moldeling of Hydrothermal Pretreatment: From Hemicellulose Hydrolysis to Biomass Size Optimization. Energy and Fuels, 2010. 24: p. 8.

5.            Ziyu Wang, J.X., and Jay J. Cheng, Modeling Biochemical Conversion of Lignocellulosic Materials for Sugar Production: A Review. BioResources, 2011. 6(4): p. 25.

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See more of this Session: Design of Biofuels and Bioproducts
See more of this Group/Topical: Computing and Systems Technology Division