Monday, April 30, 2007

Enzymatic hydrolysis of cellulose for electricity generation in a microbial fuel cell

Farzaneh Rezaei, Ag and Biological Engineering, Pennsylvania State University, 249 Ag Engineering Bldg, University Park, PA 16802, Tom L. Richard, Agricultural and Biological Engineering, Pennsylvania State University, 103 Land and Water Research Building, University Park, PA 16802, and Bruce E. Logan, Dept. of Civil and Environmental Engineering, Pennsylvania State University, 231Q Sackett Bldg, University Park, PA 16802.

Microorganisms can produce electricity by direct oxidation of organic matter in a device called a Microbial Fuel Cell (MFC). Any biodegradable material can be used in an MFC as fuel to produce electricity. These materials might be complex or simple carbohydrates, or other bio-molecules such as proteins or lipids. To date, most of the studies that have been conducted in MFCs focus on simple sugars such as glucose. Relatively little MFC research has focused on complex, insoluble carbohydrates, which comprise the major fraction of biodegradable materials in the world. The major challenge for bioconversion of lignocellulosic materials is their complex structure. They consist of cellulose, hemicellulose, and lignin in various proportions. While it is more difficult to work with complex carbohydrates as fuel for MFCs, the rewards are potentially great, since so much of the earth’s biomass is in these complex carbohydrate forms. This study used enzymatic hydrolysis to improve power production using lignocellulosic material as substrate. Enzymes were directly applied inside an anaerobic chamber where an anode, microorganisms, and cellulosic substrate were available. Results are compared to control reactors without added enzyme. Two additional controls used enzyme alone or cellulose alone to monitor the effect of each individual substrate. The maximum potential power generation is expected to be significantly higher in the enzyme amended treatments compare to the cellulose without enzyme treatment. The power output from the system was modeled based on substrates and enzyme concentration.