Electrochemical modeling of microbial fuel cells performance at different operating and structural conditions

Combining biological denitrification and electricity generation in methane-powered microbial fuel cells

Methane has been demonstrated to be a feasible substrate for electricity generation in microbial fuel cells (MFCs) and denitrifying anaerobic methane oxidation (DAMO). However, these two processes were evaluated separately in previous studies and it has remained unknown whether methane is able to simultaneously drive these processes. Here we investigated the co-occurrence and performance of these two processes in the anodic chamber of MFCs. The results showed that methane successfully fueled both electrogenesis and denitrification. Importantly, the maximum nitrate removal rate was significantly enhanced from (1.4 ± 0.8) to (18.4 ± 1.2) mg N/(L·day) by an electrogenic process. In the presence of DAMO, the MFCs achieved a maximum voltage of 610 mV and a maximum power density of 143 ± 12 mW/m². Electrochemical analyses demonstrated that some redox substances (e.g. riboflavin) were likely involved in electrogenesis and also in the denitrification process. High-throughput sequencing indicated that the methanogen Methanobacterium, a close relative of Methanobacterium espanolae, catalyzed methane oxidation and cooperated with both exoelectrogens and denitrifiers (e.g., Azoarcus). This work provides an effective strategy for improving DAMO in methane-powered MFCs, and suggests that methanogens and denitrifiers may jointly be able to provide an alternative to archaeal DAMO for methane-dependent denitrification.

Modeling and experimental investigation of the effect of carbon source on the performance of tubular microbial fuel cell

Microbial fuel cells (MFCs) serve two main purposes: clean energy production and wastewater treatment. This study examines the impact of different carbon sources on MFC performance and develops a mathematical model to replicate the polarization curve. The biological reactor employed three types of carbon sources: glucose as a simple feed, microcrystalline cellulose (MCC), and a slurry of the organic component of municipal solid waste (SOMSW) as complex feeds. The MFCs were operated in both open and closed circuit modes. The maximum open circuit voltages achieved were 695 mV for glucose, 550 mV for MCC, and 520 mV for SOMSW as substrates. The influence of the substrate in closed circuit mode was also investigated, resulting in maximum power densities of 172 mW/m2, 55.5 mW/m2, and 47.9 mW/m2 for glucose, MCC, and SOMSW as substrates, respectively. In the second section, a mathematical model was developed to depict the polarization curve while considering voltage losses, namely activation, ohmic, and concentration loss, with an average relative error (ARE) of less than 10%. The mathematical models demonstrated that the activation loss of voltage increased with the complexity of the substrate and reached its peak value when SOMSW was used as the substrate.

Identification of Emerging Industrial Biotechnology Chassis Vibrio natriegens as a Novel High Salt-Tolerant and Feedstock Flexibility Electroactive Microorganism for Microbial Fuel Cell

The development of MFC using electroactive industrial microorganisms has seen a surge of interest because of the co-generation for bioproduct and electricity production. Vibrio natriegens as a promising next-generation industrial microorganism chassis and its application for microbial fuel cells (MFC) was first studied. Mediated electron transfer was found in V. natriegens MFC (VMFC), but V. natriegens cannot secrete sufficient electron mediators to transfer electrons to the anode. All seven electron mediators supplemented are capable of improving the electronic transfer efficiency of VMFC. The media and carbon sources switching study reveals that VMFCs have excellent bioelectricity generation performance with feedstock flexibility and high salt-tolerance. Among them, 1% glycerol as the sole carbon source produced the highest power density of 111.9 ± 6.7 mW/cm². The insight of the endogenous electronic mediators found that phenazine-1-carboxamide, phenazine-1-carboxylic acid, and 1-hydroxyphenazine are synthesized by V. natriegens via the shikimate pathway and the phenazine synthesis and modification pathways. This work provides the first proof for emerging industrial biotechnology chassis V. natriegens as a novel high salt-tolerant and feedstock flexibility electroactive microorganism for MFC, and giving insight into the endogenous electron mediator biosynthesis of VMFC, paving the way for the application of V. natriegens in MFC and even microbial electrofermentation (EF).

Microbial fuel cells: a comprehensive review for beginners

Microbial fuel cells (MFCs) have shown immense potential as a one-stop solution for three major sustainability issues confronting the world today-energy security, global warming and wastewater management. MFCs represent a cross-disciplinary platform for research at the confluence of the natural and engineering sciences. The diversity of variables influencing performance of MFCs has garnered research interest across varied scientific disciplines since the beginning of this century. The increasing number of research publications has made it necessary to keep track of work being carried out by research groups across the globe and consolidate significant findings on a regular basis. Review articles are often the nodal points for beginners who are required to undertake an exploratory survey of literature to identify a suitable research problem. This 'review of reviews' is a ready-reckoner that directs readers to relevant reviews and research articles reporting significant developments in MFC research in the last two decades. The article also highlights the areas needing research attention which when addressed could take this technology a few more steps closer to practical implementation.

Modeling and optimization strategies towards performance enhancement of microbial fuel cells

Considering the complexity associated with bioelectrochemical processes, the performance of a microbial fuel cell (MFC) is governed by input operating parameters. For scaled-up applications, a MFC system needs to be modeled from engineering perspectives in terms of optimum operating conditions to get higher performance and energy recovery. Several conceptual numerical models to advanced computational simulation approaches have been developed to represent simple-form of a complex MFC system. Application of mathematical and computation models are explored to establish the relationship between operating input-variables and power output. The present review discusses about the complexity of system, modeling strategies used and reality of such modeling for scaling-up applications of MFCs. Additionally, the selection of an appropriate mathematical model reduces the computational duration and provides better understanding of the system process. It also explores the possibility and progress towards commercialization of MFCs and thus the need of development of model-based optimization and process-control approaches.

Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Microbial fuel cells (MFCs) are a promising technology for bioenergy generation and wastewater treatment. Various parameters affect the performance of dual-chamber MFCs, such as substrate flow rate and concentration. Performance can be assessed by power density ( PD ), current density ( CD ) production, or substrate removal efficiency ( SRE ). In this study, a mathematical model-based optimization was used to optimize the performance of an MFC using single- and multi-objective optimization (MOO) methods. Matlab’s fmincon and fminimax functions were used to solve the nonlinear constrained equations for the single- and multi-objective optimization, respectively. The fminimax method minimizes the worst-case of the two conflicting objective functions. The single-objective optimization revealed that the maximum PD ,   CD , and SRE were 2.04 W/m2, 11.08 A/m2, and 73.6%, respectively. The substrate concentration and flow rate significantly impacted the performance of the MFC. Pareto-optimal solutions were generated using the weighted sum method for maximizing the two conflicting objectives of PD and CD in addition to PD and SRE   simultaneously. The fminimax method for maximizing PD and CD showed that the compromise solution was to operate the MFC at maximum PD conditions. The model-based optimization proved to be a fast and low-cost optimization method for MFCs and it provided a better understanding of the factors affecting an MFC’s performance. The MOO provided Pareto-optimal solutions with multiple choices for practical applications depending on the purpose of using the MFCs.