Prediction of sustainable electricity generation in microbial fuel cell by neural network: Effect of anode angle with respect to flow direction

Abstract

This study aimed to investigate for the first time the effect of anode inclination on electricity generation integrated with biodegradation of organic substrate in a mediator-less microbial fuel cell continuously fueled with actual dairy wastewater. The influence of anode inclination was investigated at angles 0, 45 and 90° with respect to the flow direction on the MFC performance with respect to power generation and COD removal, alternatively at 1 and 2mL/min wastewater flow rate. Results revealed that maximum power generation of 486 and 369mW/m2 and COD removal efficiencies of 92 and 89% were observed when the anode was positioned perpendicularly with the flow direction at steady state conditions using wastewater flow rates of 1 and 2mL/min, respectively at external resistance of 40Ω. Lower COD removal and power generation were observed for MFCs designed with anodes positioned at 0° and 45° with respect to the feed flow direction. A three-layer artificial neural network (ANN) model was investigated in this study to predict the efficiency of the MFC in regard to power generation. Results of prediction indicated a good fitting between actual and predicted data with a high correlation coefficient (R2) of 0.99889 with negligible mean square error.