Understanding mild acid pretreatment of sugarcane bagasse through particle scale modeling. Issue 12 (10th July 2013)

• Record Type: Journal Article
• Authors: Greenwood, Ava A.; Farrell, Troy W.; O'Hara, Ian M.
• Is Part Of: Biotechnology and bioengineering. Volume 110:Issue 12(2013:Dec.)
• Page Start: 3114
• Page End: 3125
• Publication Date: 2013-07-10
• Subjects: Biotechnology -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/bit.24984
• Languages: English
• ISSNs: 0006-3592

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>ABSTRACT</title> <sec id="bit24984-sec-0001" sec-type="section"> <p>Sugarcane bagasse is an abundant and sustainable resource, generated as a by‐product of sugarcane milling. The cellulosic material within bagasse can be broken down into glucose molecules and fermented to produce ethanol, making it a promising feedstock for biofuel production. Mild acid pretreatment hydrolyses the hemicellulosic component of biomass, thus allowing enzymes greater access to the cellulosic substrate during saccharification. A particle‐scale mathematical model describing the mild acid pretreatment of sugarcane bagasse has been developed, using a volume averaged framework. Discrete population‐balance equations are used to characterise the polymer degradation kinetics, and diffusive effects account for mass transport within the cell wall of the bagasse. As the fibrous material hydrolyses over time, variations in the porosity of the cell wall and the downstream effects on the reaction kinetics are accounted for using conservation of volume arguments. Non‐dimensionalization of the model equations reduces the number of parameters in the system to a set of four dimensionless ratios that compare the timescales of different reaction and diffusion events. Theoretical yield curves are compared to macroscopic experimental observations from the literature and inferences are made as to constraints on these "unknown" parameters. These results enable connections to be made between experimental data and the underlying thermodynamics of acid pretreatment. Consequently, the results suggest that data‐fitting techniques used to obtain kinetic parameters should be carefully applied, with prudent consideration given to the chemical and physiological processes being modeled. Biotechnol. Bioeng. 2013;110: 3114–3125. © 2013 Wiley Periodicals, Inc.</p> </sec> </abstract>