Modeling and Simulation of Microbial Fuel Cells

Northwestern University, Evanston IL

Investigators

Abstract

This project would use mathematical modeling and computer simulations to help evaluate the potential capabilities of a commercial scale implementation of microbial fuel cells. The mathematical modeling we will employ is a continuum model using a combination of the level set method with the extended finite element method for solving a coupled system of reaction diffusion equations that incorporates the diffusion of various elements such as oxygen, substrates, and byproducts, as well as the growth of biomass consisting of multiple bacterial species attached to a fixed surface, or substratum. We have successfully applied this strategy to other biofilm systems such as Pseudomonas aeruginosa, a common bacterium often associated with mortality in people with cystic fibrosis, and heterotroph/autotroph symbiotic systems present in activated sludge water treatment processes. In this project, we will develop the necessary reactions and growth processes to simulate the microbial fuel cell system and use it to study various control strategies for optimizing energy production. Microbial fuel cells are an attractive potential alternative energy source that are currently only at an experimental stage. These systems take waste water streams, e.g. pig manure, and convert them directly into electricity without the use of combustion. At the same time, the water is being cleaned of harmful elements such as ammonium, that is one stage of a comprehensive water treatment process currently in use. It is estimated that microbial fuel cells have the potential to generate as much as 25% of the current worldwide power demand, all while using a negative cost energy source in waste water. Experimental systems are currently limited to bench scale reactors in closed systems that have a limited lifespan. To take these systems to the commercial scale, these systems need to be better understood for potential power per cost to demonstrate that they are feasible on that scale.