Development and optimization of a microbial fuel cells consortium by response surface methodology for the effective reduction of hexavalent chromium with power generation

Abstract

Microbial fuel cells (MFCs) present a promising green technology for wastewater treatment while simultaneously generating power. However, for MFCs to be sustainable and scalable, they require significant technological and operational improvements. This study aimed to optimize the MFC process using Response Surface Methodology (RSM), which integrates modeling techniques, optimization methodologies, experimental design, and analysis. RSM was applied to evaluate the interactions among three independent variables: the working volume of wastewater, the buffer's pH, and the bacterial consortia's inoculum size. Double-chambered MFCs were inoculated with various bacterial strains, including Pseudomonas stutzeri, Microbacterium algeriense, and Bacillus stratosphericus. The results indicated that MFC performance was significantly influenced by the interactions between (i) the volume of wastewater and buffer pH, (ii) the volume of wastewater and inoculum size, and (iii) buffer pH and inoculum size. The RSM findings identified the optimal conditions for power generation and hexavalent chromium (Cr6+) reduction as approximately 80% working volume of wastewater, a buffer pH of 6.9, and a 26% inoculum size of bacterial consortia. A strong correlation between the model predictions and experimental results confirmed the model's accuracy in capturing the interactions among the independent factors. These findings demonstrated the effectiveness of RSM in optimizing the performance of MFCs and provided valuable insights for the future development of sustainable MFC-based wastewater treatment systems.