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Microbial Electrochemical Systems for Bioelectricity Generation: Current State and Future Directions Publisher



Mohammadi F1 ; Vakilinezhaad GR2 ; Alrawahi N3 ; Gholipour S4
Authors
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Authors Affiliations
  1. 1. Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Department of Petroleum and Chemical Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman
  3. 3. Department of Mechanical and Industrial Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman
  4. 4. Department of Environmental Health Engineering, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran

Source: Results in Engineering Published:2023


Abstract

Increasing environmental pollution is a major concern, driven by fossil fuel consumption and growing energy demands. Energy production from various waste materials such as wastewater and sludge, could be proposed as a practical and appropriate solution to the energy crisis and waste disposal simultaneously. This approach not only addresses waste management but also generates different forms of bioenergy through biological treatment processes. Bioelectricity, a renewable and cost-effective energy source, is generated by electric potentials and currents that are produced or exist inside living microorganisms. In fact, bioelectricity is obtained from bioelectric potentials in various biological processes and through the conversion of chemical energy into electrical energy. Recently, the application of microbial electrochemical systems (MESs) has gained significant importance as a promising means of bioelectricity production. Various MESs leading to bioelectricity generation include microbial fuel cells (MFCs) and microbial desalination cells (MDCs). This paper explores the definitions of MESs, their detailed mechanisms, configurations, operational parameters, benefits and limitations, as well as the kinetics and thermodynamics associated with bioelectricity generation technologies. Additionally, it investigated the use of various types of artificial intelligence algorithms for modeling and optimizing biological processes for bioelectricity generation. © 2023 The Authors