Model-based design and optimization of a microbial fuel cell

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Energy production in a microbial fuel cell (MFC) is an emerging area of research, which has attracted an increased amount of attention from the scientific community. In a MFC, anodophilic microorganisms degrade organic matter and transfer electrons to the anode via nanowires or self-produced mediators, while releasing protons. Depending on the cathodic reaction, either electricity generation (MFC) or hydrogen production (MEC) can be achieved. Energy production in MFCs and MECs has been demonstrated from a variety of carbon sources, including volatile fatty acids, carbohydrates, and cellulose. Mixed microbial populations of the anodic compartment might include anodophilic, methanogenic, hydrolytic and fermentative microorganisms. MFC and MEC design might benefit from the knowledge of process dynamics, including dynamics of microbial populations. However, the existing mathematical models are focused on process electrochemistry and largely neglect microbial community complexity. The proposed research program is aimed at understanding the dynamics of MFC/MEC microbial populations through the development of a model suitable for simulating a mixed microbial population. To study process dynamics, an array of off-line and on-line experiments will be performed. In particular, on-line monitoring of substrate distribution in the anodic compartment and within the anode will be examined by multi-wavelength (3D) fluorometry. The intended application of this model includes improved design of continuous flow MFCs and MECs (i.e. anodic chamber configuration, electrode size and positioning, operating conditions), MFC stack design, and the development of feedback control algorithms for maximizing power output.