Statistical modelling of microbial fuel cells for optimization of maximum power generation efficiency using wastewater as substrate

In the current study, we have investigated the production of power from post-methanation distillery effluent (PMDE) utilising a two chamber microbial fuel cell (MFC) with batch mode parameter optimisation using response surface methodology statistical model along with box behnken design for the examination of interactive impacts of four factors, including the initial COD of the feed solution (100-1200 mg/L), pH of the anolyte (7-9), pH of the catholyte (1.5-2.5), and NaCl supplement in the anolyte (0-50 mM). Maximum power density has been anticipated by the response surface data put into the model under the conditions of 1200 mg/L COD in the feed solution, pH 8 for the anolyte, pH 1.5 for the catholyte, and a 25 mM NaCl supplement in the anolyte. According to a decent regression coefficient (R2 = 0.81) and an ANOVA test of the model's significance (p < 0.005), the power density findings from the Box-Behnken experimental design have closely connected to the response anticipated by the second-order polynomial regression model.