Determination of the effects of electrode structure and environmental conditions on the electrical performance of a microbial fuel cell by experimental and ANN approach

Microbial fuel cells are a popular field of study for alternative energy sources. It is an alternative energy source that can convert biochemical energy into electrical energy and offers many fields of study. In this thesis, it is planned to improve the operating parameters that hinder the widespread use and commercialization of microbial fuel cells and to predict predictive systems for the future. Parameters such as oxidation rate, electrode efficiency, ambient conditions and physical conditions reduce the energy performance of the cells. Within the scope of the study, the first part of the study is to examine the electrodes structurally as network structure, foam structure and plate structure. In these structural studies, different geometries were used and analyzed to understand the importance of electrode geometry. In another part of the study, different food types were compared among themselves. It was aimed to determine the optimum feeding rate by feeding a fixed food with different feeding rates and to find the optimum feeding type by using different feeding types. Another part of the study was environmental conditions. In this context, the cells were tested under different temperature conditions and their behavior was examined under different light conditions. Finally, the importance of the number of electrodes in microbial fuel cells and the effect of electrode position on performance were investigated. The obtained data were tested for predictability by ANN training in MATLAB environment. It was observed that the electrodes in microbial fuel cells are volumetrically effective and dense volumes give more successful output. Structurally, the network structure of the electrodes created high surface area and efficient energy output. Ambient conditions studies have shown that high temperature and low light wavelengths have a positive effect on cell performance. It was concluded that the increase in the number of electrodes has a positive effect on cell performance and the electrode position can be affected by the intensity of microbial activity. ANN training was performed successfully.