While many pretreatments attempt to improve the enzymatic digestibility of biomass by removing lignin, this study shows that improving the surface area accessible to cellulase is a more important factor for achieving a high sugar yield. Here we compared the pretreatment of switchgrass by two methods, cellulose solvent- and organic solvent-based lignocellulose fractionation (COSLIF) and soaking in aqueous ammonia (SAA). Following pretreatment, enzymatic hydrolysis was conducted at two cellulase loadings, 15 filter paper units (FPU)/g glucan and 3 FPU/g glucan, with and without BSA blocking of lignin absorption sites. The hydrolysis results showed that the lignin remaining after SAA had a significant negative effect on cellulase performance, despite the high level of delignification achieved with this pretreatment. No negative effect due to lignin was detected for COSLIF-treated substrate. SEM micrographs, XRD crystallinity measurements, and cellulose accessibility to cellulase (CAC) determinations confirmed that COSLIF fully disrupted the cell wall structure, resulting in a 16-fold increase in CAC, while SAA caused a 1.4-fold CAC increase. A surface plot relating the lignin removal, CAC, and digestibility of numerous samples (both pure cellulosic substrates and lignocellulosic materials pretreated by several methods) was also developed to better understand the relative impacts of delignification and CAC on glucan digestibility.
The use of hydrogen (H 2 ) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H 2 and CO 2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H 2 with a yield of two H 2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H 2 productivity was increased 3-fold to 32 mmol H 2 ·L. The productivity was further enhanced to 54 mmol H 2 ·L −1 ·h −1 by increasing reaction temperature, substrate, and enzyme concentrations-an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.hydrogen | biomass | in vitro metabolic engineering | metabolic network modeling | global sensitivity analysis
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