Review of the Process Optimization in Microbial Fuel Cell using Design of Experiment Methodology

Abstract In the last couple of decades, microbial fuel cells (MFCs) have gained importance because of its ability to generate electricity from renewable and carbon-neutral energy sources, such as wastewater. The occurrence of simultaneous biological and electrochemical processes to facilitate the electron transfer mechanism increases the process complexity. Considerable experimental and modeling techniques have been carried out to identify the different processes involved and their relative effect on electricity generation to improve the performance of the MFCs for practical applications. Among the various statistical modeling approaches, the design of experiments (DoE) is used as a robust tool to determine the relationship between variables influencing the performance of the MFCs and to perform optimization of configuration and operation of the MFCs. It has several advantages over the one-factor-at-a-time (OFAT) methodology, in terms of time and resource management as well as obtaining relevant information. This review illustrates the most popular experimental designs used in MFC-related studies. It is expected that the paper will encourage researchers to incorporate this method into their experimental studies to ensure high-quality research output.