Microbial Fuel Cell (MFC) is a bio-electrochemical system that generates electricity by anaerobic oxidation of substrates. An anode is the most critical component because the primary conversion of wastewater into electrons and protons takes place on the surface of the anode, where a biofilm is formed. This paper describes the essential properties of the anode and classifies its types according to the material used to make it. Anode material is responsible for the flow of electrons generated by the microorganism; hence biocompatibility and conductivity can considered to be the two most important properties. In this paper, the various modification strategies to improve the performance of anodes of MFC are explained through the review of researchers’ published work in this field. The shape and size of the anode turned out to be very significant as the microbial growth depends on the available surface area. The attachment of biofilm on the surface of an anode largely depends on the interfacial surface chemistry. Methods for improving MFC performance by altering the anode material, architecture, biocompatibility, and longevity are discussed with a future perspective giving special importance to the cost.

Microbial fuel cells (MFC) are an emerging technology for wastewater treatment that utilizes the metabolism of microorganisms to generate electricity from the organic matter present in water directly. The principle of MFC is the same as hydrogen fuel cell and has three main components (i.e., anode, cathode, and proton exchange membrane). The membrane separates the anode and cathode chambers and keeps the anaerobic and aerobic conditions in the two chambers, respectively. This review paper describes the state-of-the-art membrane materials particularly suited for MFC and discusses the recent development to obtain robust, sustainable, and cost-effective membranes. Nafion 117, Flemion, and Hyflon are the typical commercially available membranes used in MFC. Use of non-fluorinated polymeric membrane materials such as sulfonated silicon dioxide (S-SiO2) in sulfonated polystyrene ethylene butylene polystyrene (SSEBS), sulfonated polyether ether ketone (SPEEK) and graphene oxide sulfonated polyether ether ketone (GO/SPEEK) membranes showed promising output and proved to be an alternative material to Nafion 117. There are many challenges to selecting a suitable membrane for a scaled-up MFC system so that the technology become technically and economically viable.

This review explores recent advancements in hydrogen gas (H₂) safety through the lens of artificial intelligence (AI) techniques. As hydrogen gains prominence as a clean energy source, ensuring its safe handling becomes paramount. The paper critically evaluates the implementation of AI methodologies, including artificial neural networks (ANN), machine learning algorithms, computer vision (CV), and data fusion techniques, in enhancing hydrogen safety measures. By examining the integration of wireless sensor networks and AI for real-time monitoring and leveraging CV for interpreting visual indicators related to hydrogen leakage issues, this review highlights the transformative potential of AI in revolutionizing safety frameworks. Moreover, it addresses key challenges such as the scarcity of standardized datasets, the optimization of AI models for diverse environmental conditions, etc., while also identifying opportunities for further research and development. This review foresees faster response times, reduced false alarms, and overall improved safety for hydrogen-related applications. This paper serves as a valuable resource for researchers, engineers, and practitioners seeking to leverage state-of-the-art AI technologies for enhanced hydrogen safety systems.

Solar photovoltaic (PV) power has several advantages such as free availability, absence of rotating parts, can be easily integrated with building architecture, and need little maintenance. However, the PV cell current–voltage (I–V) characteristics are non-linear and power generated from a PV array depends on solar insolation/irradiation and panel temperature. The extracted PV output power is influenced by the accuracy with which the nonlinear power–voltage (P–V) characteristic curve is traced by the maximum power point tracking (MPPT) controller. In this paper, a bio-inspired roach infestation optimization (RIO) algorithm is proposed to extract the maximum power from the PV system (PVS). To validate the usefulness of the RIO MPPT algorithm, MATLAB/Simulink simulations are performed under varying environmental conditions, for example, step changes in solar irradiance, partial shading, and the presence of system uncertainties and load variation conditions of the PV array. Furthermore, the search performance of the RIO algorithm is examined on different unconstrained benchmark functions, and it is realized that the RIO algorithm has improved search performance in terms of finding the optimal solution and faster convergence characteristics than Particle swarm optimization (PSO). The results demonstrated that the RIO-based MPPT performs remarkably in tracking with high accuracy as the PSO, perturb and observe (P&O), and incremental conductance (IC)-based MPPT schemes.

Microbial fuel cells (MFC) are emerging technologies that can produce electricity while treating wastewater. A series of tests were carried out to evaluate the efficiency of this technology for treating dairy wastewater (DWW). The experiments used Shewanella baltica as an exoelectrogen in a small single MFC to treat simulated DWW. The impacts of various operational factors, specifically pH, hydraulic retention time (HRT), and chemical oxygen demand (COD) in the influent to the anode chamber, were investigated, and the effect of these variables on the output performance of the cell was evaluated. The best performance of the MFC was found when the pH, HRT, and COD were 8, 6.66 h, and 20,632 mg/L, respectively, in the scaled experimental setup. Under these conditions, the maximum power density and percentage removal of COD in terms of wastewater treatment ability were found to be 138 mW/m² and 71%, respectively. It may be concluded that MFCs are suitable treatment technologies for treating dairy wastewater while potentially simultaneously generating power.

Microbial fuel cells (MFCs) are a kind of bioreactor for generating electricity, facilitated by exoelectrogens while treating wastewater. The present article focuses on the performance of an air cathode plexiglass MFC in terms of chemical oxygen demand (COD) removal efficiency and power output by performing two sets of experiments. The proton exchange membrane and electrode materials were Nafion 117 and carbon felts, whereas, for stable biofilm formation on the anode surface, a pure culture of Shewanella baltica 20 was used. Firstly, sterile Luria-Bertani (LB) media containing lactate, ranging from 20 to 100 mM, was continuously fed to an MFC, and a maximum power density of 55 mW/m² was observed. Similarly, artificial wastewater with COD ranging from 3250 mg/L to 10,272 mg/L was supplied to the MFC in the second set of experiments. In this case, the maximum power density and COD removal efficiency were 12 mW/m² and 57%, respectively. In both cases, the hydraulic retention time (HRT) was 1.5 h. It was found that electricity generation depends on the characteristics of the wastewater. These initial findings confirm that the design aspects of an MFC, i.e., surface area to volume ratio, and external resistance with respect to the quality of influent need to be optimised to improve the MFC’s performance.