A brief review on factors affecting the performance of microbial fuel cell and integration of artificial intelligence
Ritesh Ojha, Jyotilagna Dash, Swati Sucharita Satpathy, Priti Chhanda Ojha, Debabrata Pradhan
Abstract
Microbial fuel cells (MFCs) represent a promising bioelectrochemical technology that enables simultaneous wastewater treatment and renewable energy generation. Unlike conventional fuel cells that require refined fuels, MFCs utilize biodegradable organic substrates often sourced from waste streams as electron donors. However, electron transfer and capture inefficiencies significantly limit power output and system performance. To address these challenges, extensive research has focused on optimizing individual components of MFCs, including the anode, cathode, membrane, electroactive microbial communities, and substrates. Innovations in electrode materials, electron transport mechanisms, membrane selectivity, and electrolyte composition are central to improving system efficiency. Furthermore, integrating MFC technology with emerging tools, such as hybrid systems, nanotechnology, additive manufacturing, artificial intelligence (AI), adaptive control systems, and synthetic biology, offers new pathways to enhance performance and scalability. This review uniquely summarizes key performance factors influencing MFCs, ranging from material science to microbial community dynamics, while highlighting the role of emerging tools like AI in predictive modelling and performance optimization. A comparative evaluation of AI techniques like artificial neural network, adaptive neuro-fuzzy inference systems, support vector regression, and long short-term memory and their integration into MFC operational parameters is presented. Furthermore, the review critically examines the real-world applicability of nanomaterials and genetic tools, assessing their sustainability in wastewater environments. By connecting classical electrochemical design with intelligent systems and sustainable engineering, this review identifies a smart-oriented pathway to advance scalable MFC deployment.