Modelling of a microbial fuel cell process

Generation of bio-energy after optimization and controlling fluctuations using various sludge activated microbial fuel cell

An aerobic microbial fuel cell (MFC) was designed to produce bio-electricity using cow manure-pretreated slurry (CM) and sewage sludge (SS). A comparative study of parametric effects on power generation for various parameters like feed ratio of wastes, pH of anode media, and electrode depth was conducted. This experiment aimed to identify the most important system parameters and optimize them to develop a suitable controller for a stable output. Power production reached its maximum at an electrode depth of 7 cm, a pH of 6, and a feed ratio of 2:1 in the CM + SS system before applying the controller. Response surface methodology (RSM) was practiced to explore the relationships between various parameters and the response using MINITAB software. The regression equation of the most productive system deduced from the RSM result has an R2 value of 85.3%. The results show that an ON/OFF controller works satisfactorily in this study. The highest energy-generating setup has a chemical oxygen demand (COD) removal efficiency of 45%. The morphology and content of the used wastes indicate that they can be recycled in other applications.

Model development of bioelectrochemical systems: A critical review from the perspective of physiochemical principles and mathematical methods

Bioelectrochemical systems (BESs) are promising devices for wastewater treatment and bio-energy production. Since various processes are interacted and affect the overall performance of the device, the development of theoretical modeling is an efficient approach to understand the fundamental mechanisms that govern the performance of the BES. This review aims to summarize the physiochemical principle and mathematical method in BES models, which is of great importance for the establishment of an accurate model while has received little attention in previous reviews. In this review, we begin with a classification of existing models including bioelectrochemical models, electronic models, and machine learning models. Subsequently, physiochemical principles and mathematical methods in models are discussed from two aspects: one is the description of methodology how to build a framework for models, and the other is to further review additional methods that can enrich model functions. Finally, the advantages/disadvantages, extended applications, and perspectives of models are discussed. It is expected that this review can provide a viewpoint from methodologies to understand BES models.

A Catalytic Effectiveness Factor for a Microbial Electrolysis Cell Biofilm Model

The aim of this work is to propose a methodology to obtain an effectiveness factor for biofilm in a microbial electrolysis cell (MEC) system and use it to reduce a partial differential equation (PDE) biofilm MEC model to an ordinary differential equation (ODE) MEC model. The biofilm mass balances of the different species are considered. In addition, it is considered that all the involved microorganisms are attached to the anodic biological film. Three effectiveness factors are obtained from partial differential equations describing the spatial distributions of potential and substrate in the biofilm. Then, a model reduction is carried out using the global mass balances of the different species in the system. The reduced model with three uncertain but bounded effectiveness factors is evaluated numerically and analyzed in the sense of stability and parametric sensibility to demonstrate its applicability. The reduced ODE model is compared with a validated model taken from the literature, and the results are in good agreement. The biofilm effectiveness factor in MEC systems can be extended to the reduction of PDE models to obtain ODE models that are commonly used in optimization and control problems.

3D Conducting Polymeric Membrane and Scaffold Saccharomyces cerevisiae Biofilms to Enhance Energy Conversion in Microbial Fuel Cells

Microbial fuel cells (MFCs) can spontaneously convert chemical energy into electricity using biocatalytic microorganisms and organic matter as fuel feedstocks. Three-dimensional cross-linked poly(vinyl alcohol)-based membranes were produced by a sol-gel method under homogeneous catalysis and used as the electrolyte to facilitate effective proton conduction. Under dry conditions, these polymeric membranes showed high water uptake (120%) and ionic conductivity (2.815 mS cm^-1). In the anode compartment, the scaffold Saccharomyces cerevisiae film biocatalysts were used to improve electron transfer to the cathode, using three major configurations to generate a higher power output. It was found that the graphene anchoring, red light (RL) stimulation, and methylene blue (MB) mediation-enhanced device performance. The electrochemically derived graphene improved the power and current density by 40% because of its high conductivity. The RL stimulation increased the power density by 80% because of a shortened electron flow path to complex III. The MB mediation also yielded a higher current density by 340% because MB can bypass the electron flow from complex II to cytochrome c and transfer electrons directly to complex III. The individual and collective increase in power output was due to more efficient electron flow from the electronic network permeating the biofilm. The generated electrons were transferred either to graphene as an energy-efficient direct transfer mode or to methylene blue as a long-range redox mediator for indirect transfer. Red light stimulation enhanced oxygen utilization efficiency and stimulated electrons in redox proteins enhancing electron flux. These processes generated higher power through the more efficient generation of electrons and faster transport to the external circuit. As society migrates from gasoline consumption to low carbon-based fuels, the MFCs become important in producing electrical energy with low net emissions.

Fundamental understanding of microbial fuel cell technology: Recent development and challenges

The research on microbial fuel cells (MFCs) is rising tremendously but its commercialization is restricted by several microbiological, material, and economic constraints. Hence, a systematic assessment of the research articles published previously focusing on potential upcoming directions in this field is necessary. A detailed multi-perspective analysis of various techniques for enhancing the efficiency of MFC in terms of electric power production is presented in this paper. A brief discussion on the central aspects of different issues are preceded by an extensive analysis of the strategies that can be introduced to optimize power generation and reduce energy losses. Various applications of MFCs in a broad spectrum ranging from biomedical to underwater monitoring rather than electricity production and wastewater treatment are also presented followed by relevant possible case studies. Mathematical modeling is used to understand the concepts that cannot be understood experimentally. These methods relate electrode geometries to microbiological reactions occurring inside the MFC chamber, which explains the system's behavior and can be improved. Finally, directions for future research in the field of MFCs have been suggested. This article can be beneficial for engineers and researchers concerned about the challenges faced in the application of MFC.

Bio-Electrochemical System Depollution Capabilities and Monitoring Applications: Models, Applicability, Advanced Bio-Based Concept for Predicting Pollutant Degradation and Microbial Growth Kinetics via Gene Regulation Modelling

Microbial fuel cells (MFC) are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling-up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod-type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio-based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored.

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.

Glucose-Oxygen Biofuel Cell with Biotic and Abiotic Catalysts: Experimental Research and Mathematical Modeling

The demand for alternative sources of clean, sustainable, and renewable energy has been a focus of research around the world for the past few decades. Microbial/enzymatic biofuel cells are one of the popular technologies for generating electricity from organic substrates. Currently, one of the promising fuel options is based on glucose due to its multiple advantages: high energy intensity, environmental friendliness, low cost, etc. The effectiveness of biofuel cells is largely determined by the activity of biocatalytic systems applied to accelerate electrode reactions. For this work with aerobic granular sludge as a basis, a nitrogen-fixing community of microorganisms has been selected. The microorganisms were immobilized on a carbon material (graphite foam, carbon nanotubes). The bioanode was developed from a selected biological material. A membraneless biofuel cell glucose/oxygen, with abiotic metal catalysts and biocatalysts based on a microorganism community and enzymes, has been developed. Using methods of laboratory electrochemical studies and mathematical modeling, the physicochemical phenomena and processes occurring in the cell has been studied. The mathematical model includes equations for the kinetics of electrochemical reactions and the growth of microbiological population, the material balance of the components, and charge balance. The results of calculations of the distribution of component concentrations over the thickness of the active layer and over time are presented. The data obtained from the model calculations correspond to the experimental ones. Optimization for fuel concentration has been carried out.

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.

A Review of Control-Oriented Bioelectrochemical Mathematical Models of Microbial Fuel Cells

A microbial fuel cell (MFC) is a potentially viable renewable energy option which promises effective and commercial harvesting of electrical power by bacterial movement and at the same time also treats wastewater. Microbial fuel cells are complicated devices and therefore research in this field needs interdisciplinary knowledge and involves diverse areas such as biological, chemical, electrical, etc. In recent decades, rapid strides have taken place in fuel cell research and this technology has become more efficient. For effective usage, such devices need advanced control techniques for maintaining a balance between substrate supply, mass, charge, and external load. Most of the research work in this area focuses on experimental work and have been described from the design perspective. Recently, the development in mathematical modeling of such cells has taken place which has provided a few mathematical models. Mathematical modeling provides a better understanding of the operations and the dynamics of MFCs, which will help to develop control and optimization strategies. Control-oriented bio-electrochemical models with mass and charge balance of MFCs facilitate the development of advanced nonlinear controllers. This work reviews the different mathematical models of such cells available in the literature and then presents suitable parametrization to develop control-oriented bio-electrochemical models of three different types of cells with their uncertain parameters.

Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach

Microbial fuel cells (MFCs) is a promising technology that is able to simultaneously produce bioenergy and treat wastewater. Their potential large-scale application is still limited by the need of optimising their power density. The aim of this study is to simulate the absolute power output by ceramic-based MFCs fed with human urine by using a fuzzy inference system in order to maximise the energy harvesting. For this purpose, membrane thickness, anode area and external resistance, were varied by running a 27-parameter combination in triplicate with a total number of 81 assays performed. Performance indices such as R² and variance account for (VAF) were employed in order to compare the accuracy of the fuzzy inference system designed with that obtained by using nonlinear multivariable regression. R² and VAF were calculated as 94.85% and 94.41% for the fuzzy inference system and 79.72% and 65.19% for the nonlinear multivariable regression model, respectively. As a result, these indices revealed that the prediction of the absolute power output by ceramic-based MFCs of the fuzzy-based systems is more reliable than the nonlinear multivariable regression approach. The analysis of the response surface obtained by the fuzzy inference system determines that the maximum absolute power output by the air-breathing set-up studied is 450  μ W when the anode area ranged from 160 to 200 cm², the external loading is approximately 900 Ω and a membrane thickness of 1.6 mm, taking into account that the results also confirm that the latter parameter does not show a significant effect on the power output in the range of values studied.

Microbial fuel cells as an alternative energy source: current status

Microbial fuel cell (MFC) technology is an emerging area for alternative renewable energy generation and it offers additional opportunities for environmental bioremediation. Recent scientific studies have focused on MFC reactor design as well as reactor operations to increase energy output. The advancement in alternative MFC models and their performance in recent years reflect the interests of scientific community to exploit this technology for wider practical applications and environmental benefit. This is reflected in the diversity of the substrates available for use in MFCs at an economically viable level. This review provides an overview of the commonly used MFC designs and materials along with the basic operating parameters that have been developed in recent years. Still, many limitations and challenges exist for MFC development that needs to be further addressed to make them economically feasible for general use. These include continued improvements in fuel cell design and efficiency as well scale-up with economically practical applications tailored to local needs.

Modeling Microbial Electrosynthesis

Mathematical modeling is an overarching approach for assessing the complexity of microbial electrosynthesis (MES) and for complementing the relevant experimental research. By describing and linking compartments, components, and processes with appropriate mathematical equations, MES and the corresponding bioelectrodes and complete bioelectrochemical systems can be analyzed and predicted across several temporal and local scales. Thereby, insights into fundamental phenomena and mechanisms, in addition to process engineering and design can be obtained. However, a substantial lack of knowledge about extracellular electron transfer mechanisms and electrotrophic microorganisms presumably prevented the development of adequate models of MES, especially of biocathodes, so far. To propel efforts regarding this demanding task, this chapter provides a comprehensive overview of the relevant compartments, components and processes, appropriate model strategies, and a discussion on potential modeling pitfalls. By adapting an established approach to assessing the energetics of microorganism, an instruction for calculating stoichiometry, thermodynamics, and kinetics, with the example of electro-autotrophic growth at cathodes, is presented. Models of bioanodes and fundamental electrochemical equations are described to provided strategies for calculating cathodic electron-uptake reactions and connecting them to the microbial metabolism. Finally, differential equations are detailed for coupling the distinct compartments of a bioelectrochemical system. Although MES comprises anodic and cathodic reactions, the present chapter focuses on biocathodes representing a functional connection between cathode and electron-accepting microorganisms. Graphical Abstract.

No enhancement of cyanobacterial bloom biomass decomposition by sediment microbial fuel cell (SMFC) at different temperatures

The sediment microbial fuel cell (SMFC) has potential application to control the degradation of decayed cyanobacterial bloom biomass (CBB) in sediment in eutrophic lakes. In this study, temperatures from 4 to 35 °C were investigated herein as the major impact on SMFC performance in CBB-amended sediment. Under low temperature conditions, the SMFC could still operate, and produced a maximum power density of 4.09 mW m^-2 at 4 °C. Coupled with the high substrate utilization, high output voltage was generated in SMFCs at high temperatures. The application of SMFC affected the anaerobic fermentation progress and was detrimental to the growth of methanogens. At the same time, organic matter of sediments in SMFC became more humified. As a result, the fermentation of CBB was not accelerated with the SMFC application, and the removal efficiency of the total organic matter was inhibited by 5% compared to the control. Thus, SMFC could operate well year round in sediments with a temperature ranging from 4 to 35 °C, and also exhibit practical value by inhibiting quick CBB decomposition in sediments in summer against the pollution of algae organic matter.

Application of the finite difference method to model pH and substrate concentration in a double-chamber microbial fuel cell

The purpose of this study was to develop a mathematical model that can describe glucose degradation in a microbial fuel cell (MFC) with the use of finite difference approach. The dynamic model can describe both substrate and pH changes in the anode chamber of a double-chamber MFC. It was developed using finite differences and incorporates basic mass transfer concepts. Model simulation results could fit the experimental data for substrate consumption well, while there was a moderate discrepancy (maximum 0.11 pH unit) between the simulated pH and the experimental data. A parametric sensitivity analysis showed that increases in acetate and propionate consumption rates can cause great decrease in chemical oxygen demand (COD) in the anode chamber, while an increase in glucose consumption rate does not result in significant changes of COD reduction. Therefore, the rate limitation steps of glucose degradation are the oxidations of secondary degradation products of glucose (acetate and propionate). Due to the buffering effect of the nutrient solution, the increases in glucose, acetate and propionate consumption rates did not result in much change on pH of the anode chamber.

Electrochemically active biofilms: facts and fiction. A review

This review examines the electrochemical techniques used to study extracellular electron transfer in the electrochemically active biofilms that are used in microbial fuel cells and other bioelectrochemical systems. Electrochemically active biofilms are defined as biofilms that exchange electrons with conductive surfaces: electrodes. Following the electrochemical conventions, and recognizing that electrodes can be considered reactants in these bioelectrochemical processes, biofilms that deliver electrons to the biofilm electrode are called anodic, ie electrode-reducing, biofilms, while biofilms that accept electrons from the biofilm electrode are called cathodic, ie electrode-oxidizing, biofilms. How to grow these electrochemically active biofilms in bioelectrochemical systems is discussed and also the critical choices made in the experimental setup that affect the experimental results. The reactor configurations used in bioelectrochemical systems research are also described and the authors demonstrate how to use selected voltammetric techniques to study extracellular electron transfer in bioelectrochemical systems. Finally, some critical concerns with the proposed electron transfer mechanisms in bioelectrochemical systems are addressed together with the prospects of bioelectrochemical systems as energy-converting and energy-harvesting devices.

The effect of flavin electron shuttles in microbial fuel cells current production

The effect of electron shuttles on electron transfer to microbial fuel cell (MFC) anodes was studied in systems where direct contact with the anode was precluded. MFCs were inoculated with Shewanella cells, and flavins used as the electron shuttling compound. In MFCs with no added electron shuttles, flavin concentrations monitored in the MFCs' bulk liquid increased continuously with FMN as the predominant flavin. The maximum concentrations were 0.6 microM for flavin mononucleotide and 0.2 microM for riboflavin. In MFCs with added flavins, micro-molar concentrations were shown to increase current and power output. The peak current was at least four times higher in MFCs with high concentrations of flavins (4.5-5.5 microM) than in MFCs with low concentrations (0.2-0.6 microM). Although high power outputs (around 150 mW/m(2)) were achieved in MFCs with high concentrations of flavins, a Clostridium-like bacterium along with other reactor limitations affected overall coulombic efficiencies (CE) obtained, achieving a maximum CE of 13%. Electron shuttle compounds (flavins) permitted bacteria to utilise a remote electron acceptor (anode) that was not accessible to the cells allowing current production until the electron donor (lactate) was consumed.

Performance of microbial fuel cell subjected to variation in pH, temperature, external load and substrate concentration

During field application, the microbial fuel cell (MFC) will be exposed to variations in operating parameters. Hence, the performance of MFC, exposed to variation in temperature, pH, external resistance and influent chemical oxygen demand (COD), was investigated in the terms of coulombic efficiency (CE) and COD removal efficiency, while treating a synthetic wastewater. The performance was analyzed under two temperature ranges such as 20-35 degrees C and 8-22 degrees C. Operation under higher temperature range favored higher COD removal efficiency of 90% and lower current (0.7 mA) and CE (1.5%). At lower temperature range, although the COD removal efficiency of MFC decreased (59%), it gave higher current (1.4 mA) and CE (5%). The highest current was generated at pH of 6.5 in the anodic chamber with CE of 4%. Higher pH difference between anodic and cathodic electrolyte favored higher current and voltage. Within the range of COD tested (100-600 mg/l), linear correlation was observed between the current and substrate removed.

Kinetics of consumption of fermentation products by anode-respiring bacteria

We determined the kinetic response of a community of anode-respiring bacteria oxidizing a mixture of the most common fermentation products: acetate, butyrate, propionate, ethanol, and hydrogen. We acclimated the community by performing three consecutive batch experiments in a microbial electrolytic cell (MEC) containing a mixture of the fermentation products. During the consecutive-batch experiments, the coulombic efficiency and start-up period improved with each step. We used the acclimated biofilm to start continuous experiments in an MEC, in which we controlled the anode potential using a potentiostat. During the continuous experiments, we tested each individual substrate at a range of anode potentials and substrate concentrations. Our results show low current densities for butyrate and hydrogen, but high current densities for propionate, acetate, and ethanol (maximum values are 1.6, 9.0, and 8.2 A/m(2), respectively). Acetate showed a high coulombic efficiency (86%) compared to ethanol and propionate (49 and 41%, respectively). High methane concentrations inside the MEC during ethanol experiments suggest that methanogenesis is one reason why the coulombic efficiency was lower than that of acetate. Our results provide kinetic parameters, such as the anode overpotential, the maximum current density, and the Monod half-saturation constant, that are needed for model development when using a mixture of fermentation products. When we provided no electron donor, we measured current due to endogenous decay of biomass (approximately 0.07 A/m(2)) and an open-cell potential (-0.54 V vs Ag/AgCl) associated with biomass components active in endogenous respiration.

A computational model for biofilm-based microbial fuel cells

This study describes and evaluates a computational model for microbial fuel cells (MFCs) based on redox mediators with several populations of suspended and attached biofilm microorganisms, and multiple dissolved chemical species. A number of biological, chemical and electrochemical reactions can occur in the bulk liquid, in the biofilm and at the electrode surface. The evolution in time of important MFC parameters (current, charge, voltage and power production, consumption of substrates, suspended and attached biomass growth) has been simulated under several operational conditions. Model calculations evaluated the effect of different substrate utilization yields, standard potential of the redox mediator, ratio of suspended to biofilm cells, initial substrate and mediator concentrations, mediator diffusivity, mass transfer boundary layer, external load resistance, endogenous metabolism, repeated substrate additions and competition between different microbial groups in the biofilm. Two- and three-dimensional model simulations revealed the heterogeneous current distribution over the planar anode surface for younger and patchy biofilms, but becoming uniform in older and more homogeneous biofilms. For uniformly flat biofilms one-dimensional models should give sufficiently accurate descriptions of produced currents. Voltage- and power-current characteristics can also be calculated at different moments in time to evaluate the limiting regime in which the MFC operates. Finally, the model predictions are tested with previously reported experimental data obtained in a batch MFC with a Geobacter biofilm fed with acetate. The potential of the general modeling framework presented here is in the understanding and design of more complex cases of wastewater-fed microbial fuel cells.

Quantitative Comparison of the Signals of an Electrochemical Bioactivity Sensor During the Cultivation of Different Microorganisms

The microbial activity of different microorganisms was determined by means of an electrochemical bioactivity sensor (BAS). The BAS is based on a biofuel cell and was used for analytical purposes. Online determination of microbial activity using the BAS demonstrated that when different microorganisms with different metabolic pathways were cultivated, a distinct activity signal was detectable with all organisms applied. Furthermore, the results permitted a quantitative comparison of the BAS signals. Among other findings it was shown that the quotient of the BAS signal and the utilized glucose varied from 0.16-29.08 mV g(-1), the quotient of the maximum BAS signal and the released energy of the reaction exhibited a lower variation of 0.07-0.19 mV kJ(-1). Furthermore it was demonstrated that the highest BAS signals could be measured during anaerobic E. coli fermentations, the reason being the formation of electroactive fermentation products, such as formic acid and H(2).

Procedure for determining maximum sustainable power generated by microbial fuel cells

Power generated by microbial fuel cells is computed as a product of current passing through an external resistor and voltage drop across this resistor. If the applied resistance is very low, then high instantaneous power generated by the cell is measured, which is not sustainable; the cell cannot deliver that much power for long periods of time. Since using small electrical resistors leads to erroneous assessment of the capabilities of microbial fuel cells, a question arises: what resistor should be used in such measurements? To address this question, we have defined the sustainable power as the steady state of power delivery by a microbial fuel cell under a given set of conditions and the maximum sustainable power as the highest sustainable power that a microbial fuel cell can deliver under a given set of conditions. Selecting the external resistance that is associated with the maximum sustainable power in a microbial fuel cell (MFC) is difficult because the operator has limited influence on the main factors that control power generation: the rate of charge transfer at the current-limiting electrode and the potential established across the fuel cell. The internal electrical resistance of microbial fuel cells varies, and it depends on the operational conditions of the fuel cell. We have designed an empirical procedure to predict the maximum sustainable power that can be generated by a microbial fuel cell operated under a given set of conditions. Following the procedure, we change the external resistors incrementally, in steps of 500 omega every 10, 60, or 180 s and measure the anode potential, the cathode potential, and the cell current. Power generated in the microbial fuel cell that we were using was limited by the anodic current. The anodic potential was used to determine the condition where the maximum sustainable power is obtained. The procedure is simple, microbial fuel cells can be characterized within an hour, and the results of the measurements can serve many purposes, such as: (1) estimating power generation in various MFCs, (2) comparing power generation in MFCs using different electroactive reactants, (3) quantifying the effects of the operational regime on the power generation in MFCs, and finally, (4) the purpose for which the procedure was designed, optimizing the performance of existing MFCs.

Wireless sensors powered by microbial fuel cells

Monitoring parameters characterizing water quality, such as temperature, pH, and concentrations of heavy metals in natural waters, is often followed by transmitting the data to remote receivers using telemetry systems. Such systems are commonly powered by batteries, which can be inconvenient at times because batteries have a limited lifetime and must be recharged or replaced periodically to ensure that sufficient energy is available to power the electronics. To avoid these inconveniences, a microbial fuel cell was designed to power electrochemical sensors and small telemetry systems to transmit the data acquired by the sensors to remote receivers. The microbial fuel cell was combined with low-power, high-efficiency electronic circuitry providing a stable power source for wireless data transmission. To generate enough power for the telemetry system, energy produced by the microbial fuel cell was stored in a capacitor and used in short bursts when needed. Since commercial electronic circuits require a minimum 3.3 V input and our cell was able to deliver a maximum of 2.1 V, a DC-DC converter was used to boost the potential. The DC-DC converter powered a transmitter, which gathered the data from the sensor and transmitted it wirelessly to a remote receiver. To demonstrate the utility of the system, temporal variations in temperature were measured, and the data were wirelessly transmitted to a remote receiver.

A glucose/hydrogen peroxide biofuel cell that uses oxidase and peroxidase as catalysts by composite bulk-modified bioelectrodes based on a solid binding matrix

An improved composite bulk-modified bioelectrode setup based on a solid binding matrix (SBM) has been used to develop a glucose/hydrogen peroxide biofuel cell. Fuel is combined through a catalytically promoted reaction with oxygen into and oxidized species and electricity. The present work explores the feasibility of a sugar-feed biofuel cell based on SBM technology. The biofuel cell that utilizes mediators as electron transporters from the glucose oxidation pathway of the enzyme directly to electrodes is considered in this work. The anode was a glucose oxidase (GOx, EC 1.1.3.4)/ferrocene-modified SBM/graphite composite electrode. The cathode was a horseradish peroxidase (HRP, EC 1.11.1.7)/ferrocene-modified SBM/graphite composite electrode. The composite transducer material was layered on a wide polymeric surface to obtain the biomodified electrodic elements, anodes and cathodes and were assembled into a biofuel cell using glucose and H(2)O(2) as the fuel substrate and the oxidizer. The electrochemical properties and the characteristics of single composite bioelectrodes are described. The open-circuit voltage of the cell was 0.22 V, and the power output of the cell was 0.15 microW/cm(2) at 0.021 V. The biofuel cell proved to be stable for an extended period of continuous work (30 days). The reproducibility of the biotransducers fabrication was also investigated. In addition, an application of presented biofuel cell, e.g. the use of hydrolyzed corn syrup as renewable biofuels, was discussed.