Novel Analytical Microbial Fuel Cell Design for Rapid in Situ Optimisation of Dilution Rate and Substrate Supply Rate, by Flow, Volume Control and Anode Placement

Microbial fuel cell systems; developments, designs, efficiencies, and trends: A comparative study between the conventional and innovative systems

The microbial fuel cell (MFC) technology has appeared in the late 20th century and received considerable attention over the last decade due to its multiple and unique potential in converting the substrates into electricity and valuable productions. Extensive efforts have been paid to improve the MFCs performance, leading to the publication of a massive amount of research that developed various aspects of these systems. Most of these improvements have focused on optimization parameters, which is currently inappropriate to provide an innovational developing vision for MFC systems. The convergent results in most of the previous conventional studies (12,643 studies according to the WOS database) have reduced the value of MFCs by drawing an incomplete image for the performance of the systems. Therefore, this paper aimed to provide a comprehensive comparison between the highly reliable studies that innovatively developed the MFC systems and the conventional MFCs studies. The current paper discusses the novel MFCs development history, designs, efficiency, and challenges compared to conventional MFCs. The discussion has displayed the high efficiency of the novel MFCs in removing over 90% of substrates and generating power of 800 mW m^-2. The paper also analyzed the literature trends, history and suggested recommendations for future studies. This is the first paper highlighting the substantial differences between the innovative and conventional MFC systems, nominating it to be a vital reference for novel MFCs studies in the future.

Development of a Bio-Digital Interface Powered by Microbial Fuel Cells

This paper reports the first relatable bio-digital interface powered by microbial fuel cells (MFCs) that was developed to inform the public and introduce the concept of using live microbes as waste processors within our homes and cities. An innovative design for the MFC and peripherals system was built as a digital data generator and bioreactor, with a custom-built energy-harvesting controller that was connected to the system to enable efficient system operation using adaptive dynamic cell reconfiguration and transmit data for the bio-digital interface. This system has accomplished multiple (parallel) tasks such as electricity generation, wastewater treatment and autonomous operation. Moreover, the controller demonstrated that microbial behaviour and consequent system operation can benefit from smart algorithms. In addition to these technical achievements, the bio-digital interface is a site for the production of digital art that aims to gain acceptance from a wider-interest community and potential audiences by showcasing the capabilities of living microorganisms in the context of green technologies.

Microbial fuel cells and their electrified biofilms

Bioelectrochemical systems (BES) represent a wide range of different biofilm-based bioreactors that includes microbial fuel cells (MFCs), microbial electrolysis cells (MECs) and microbial desalination cells (MDCs). The first described bioelectrical bioreactor is the Microbial Fuel Cell and with the exception of MDCs, it is the only type of BES that actually produces harvestable amounts of electricity, rather than requiring an electrical input to function. For these reasons, this review article, with previously unpublished supporting data, focusses primarily on MFCs. Of relevance is the architecture of these bioreactors, the type of membrane they employ (if any) for separating the chambers along with the size, as well as the geometry and material composition of the electrodes which support biofilms. Finally, the structure, properties and growth rate of the microbial biofilms colonising anodic electrodes, are of critical importance for rendering these devices, functional living 'engines' for a wide range of applications.

Statistical Modeling and Performance Optimization of a Two-Chamber Microbial Fuel Cell by Response Surface Methodology

Microbial fuel cell, as a promising technology for simultaneous power production and waste treatment, has received a great deal of attention in recent years; however, generation of a relatively low power density is the main limitation towards its commercial application. This study contributes toward the optimization, in terms of maximization, of the power density of a microbial fuel cell by employing response surface methodology, coupled with central composite design. For this optimization study, the interactive effect of three independent parameters, namely (i) acetate concentration in the influent of anodic chamber; (ii) fuel feed flow rate in anodic chamber; and (iii) oxygen concentration in the influent of cathodic chamber, have been analyzed for a two-chamber microbial fuel cell, and the optimum conditions have been identified. The optimum value of power density was observed at an acetate concentration, a fuel feed flow rate, and an oxygen concentration value of 2.60 mol m−3, 0.0 m3, and 1.00 mol m−3, respectively. The results show the achievement of a power density of 3.425 W m−2, which is significant considering the available literature. Additionally, a statistical model has also been developed that correlates the three independent factors to the power density. For this model, R2, adjusted R2, and predicted R2 were 0.839, 0.807, and 0.703, respectively. The fact that there is only a 3.8% error in the actual and adjusted R2 demonstrates that the proposed model is statistically significant.

A review of the operating parameters on the microbial fuel cell for wastewater treatment and electricity generation

Environmental and economic considerations suggest a more efficient and comprehensive use of biomass for bioenergy production. One of the most attractive technologies is the microbial fuel cell using the catabolic activity of microorganisms to generate electricity from organic matter. The microbial fuel cell (MFC) has operational benefits and higher performance than current technologies for producing energy from organic materials because it converts electricity from the substrate directly (at ambient temperature). However, MFCs are still not suitable for high energy demand due to practical limitations. The overall performance of an MFC depends on the electrode material, the reactor design, the operating parameters, substrates, and microorganisms. Furthermore, the optimization of the parameters will lead to the commercial development of this technology in the near future. The simultaneous effect of the parameters on each other (intensifier or attenuator) has also been investigated. The investigated parameters in this study include temperature, pH, flow rate and hydraulic retention time, mode, external resistance, and initial concentration.

The influential role of external electrical load in microbial fuel cells and related improvement strategies: A review

The scope of the currentreviewis to discuss and evaluate the role of the external electrical load/resistor (EEL) on the overall behavior and functional properties of microbial fuel cells (MFCs). In this work, a comprehensive analysis is made by considering various levels of MFC architecture, such as electric and energy harvesting efficiency, anode electrode potential shifts, electro-active biofilm formation, cell metabolism and extracellular electron transfer mechanisms, as a function of the EEL and its control strategies. It is outlined that taking the regulation of EEL into account at MFC optimization is highly beneficial, and in order to support this step, in this review, a variety of guidelines are collected and analyzed.

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.

Leachate treatment and electricity generation using an algae-cathode microbial fuel cell with continuous flow through the chambers in series

Algae-cathode microbial fuel cells (MFCs) with various hydraulic retention times (HRTs) were investigated for electricity generation, and chemical oxygen demand (COD) and nutrient removal from diluted landfill leachate (15% v/v). The cell voltage and dissolved oxygen (DO) in the cathode were considerably affected by the HRT. The highest cell voltage was 303 mV at 20-h HRT, and DO concentration of 5.3 mg/L was only observed at 60-h HRT. Nutrient removal increased with increasing HRTs, and the maximum removal efficiency was 76.4% and 86.3% at 60-h HRT for ammonium and phosphorus, respectively. The highest COD removal of 26% was observed at 60-h HRT. The dominant phyla in the cathode were Proteobacteria, Cyanobacteria, Bacteroidetes, and Chlorophyta, which could have contributed to electricity generation and nutrient removal. This study suggests that an algae-cathode MFC with an appropriate HRT can continuously generate electricity and simultaneously remove nutrients from real leachate wastewater in field applications.

A Time-Interleave-Based Power Management System with Maximum Power Extraction and Health Protection Algorithm for Multiple Microbial Fuel Cells for Internet of Things Smart Nodes

Microbial Fuel Cell (MFC) technology is a novel Energy Harvesting (EH) source that can transform organic substrates in wastewater into electricity through a bioelectrochemical process. However, its limited output power available per liter is in the range of a few milliwatts, which results very limited to be used by an Internet of Things (IoT) smart node that could require power in the order of hundreds of milliwatts when in full operation. One way to reach a usable power output is to connect several MFCs in series or parallel; nevertheless, the high output characteristic resistance of MFCs and differences in output voltage from multiple MFCs, dramatically worsens its power efficiency for both series and parallel arrangements. In this paper, a Power Management System (PMS) is proposed to allow maximum power harvesting from multiple MFCs while providing a regulated output voltage. To enable a more efficient and reliable power-harvesting process from multiple MFCs that considers the biochemical limitations of the bacteria to extend its lifetime, a power ranking and MFC health-protection algorithm using an interleaved EH operation was implemented in a PIC24F16KA102 microcontroller. A power extraction sub-block of the system includes an ultra-low-power BQ25505 step-up DC-DC converter, which integrates Maximum Power Point Tracking (MPPT) capabilities. The maximum efficiency measured of the PMS was ~50.7%. The energy harvesting technique presented in this work was tested to power an internet-enabled temperature-sensing smart node.