Microbial Fuel Cell Biosensor Research Articles

The effect of inoculum source of different pollution levels on the performances of microbial fuel cell biosensors

Selection of inoculum sources is a key factor in constructing microbial fuel cells (MFCs), and the property of inoculum sources is greatly affected by the degree of environmental pollution. However, limited attention has been paid to how these differences affect the response of MFC biosensors. Here the effects of inoculum sources with varying pollution levels on the performances of constructed MFCs were evaluated, and the microbial communities were analyzed before and after inoculation. The results showed significant differences in the detection of biochemical oxygen demand (BOD) and toxicity (Cu2+) among the five groups of MFC biosensors. Combined with the data of the microbial community, the results indicated that the increase rate of the initial start-up voltage is related to the abundance of original electroactive bacteria (EAB) in the inoculum source. The higher the abundance of EAB, the faster increase rate in the initial start-up voltage and the shorter start-up time. The difference in the detection range of the BOD should be related to the ability of the microbial communities to withstand the organic shock loads. The microbial community's tolerance to Cu2+ was affected by the original water quality of the inoculum source. The high metal ion content leads to low sensitivity of MFC biosensor to Cu2+ ion. Enterobacteriaceae were abundant in all the five groups of MFCs, indicating that the dominant bacteria can be enriched in MFC anode biofilms with the inoculum sources of different pollution levels. The microbial community compositions of the anode biofilms were affected by the inoculum sources of different pollution levels, which in turn resulted in the differences in MFCs performances.

Impact of Air-Cathodes on Operational Stability of Single-Chamber Microbial Fuel Cell Biosensors for Wastewater Monitoring

The increasing global water pollution leads to the need for urgent development of rapid and accurate water quality monitoring methods. Microbial fuel cells (MFCs) have emerged as real-time biosensors for biochemical oxygen demand (BOD), but they grapple with several challenges, including issues related to reproducibility, operational stability, and cost-effectiveness. These challenges are substantially shaped by the selection of an appropriate air-breathing cathode. Previous studies indicated a critical influence of the cathode on both the enduring electrochemical performance of MFCs and the taxonomic diversity at the electroactive anode. However, the effect of different gas diffusion electrodes (GDE) on 3D-printed single-chamber MFCs for BOD biosensing application and its effect on the bioelectroactive anode was not investigated before. Our study focuses on comparing GDE cathode materials to enhance MFC performance for precise and rapid BOD analysis in wastewater. We examined for over 120 days two Pt-coated air-breathing cathodes with distinct carbonaceous gas diffusion layers (GDLs) and catalyst layers (CLs): cost-effective carbon paper (CP) with hand-coated CL and more expensive woven carbon cloth (CC) with CL pre-applied by the supplier. The results show significant differences in electrochemical characteristics and anodic biofilm composition between MFCs with CP and CC GDE cathodes. CP-MFCs exhibited lower sensitivity (16.6 C L mg−1 m−2) and a narrower dynamic range (25 to 600 mg L−1), attributed to biofouling-related degradation of the GDE. In contrast, CC-MFCs demonstrated superior performance with higher sensitivity (37.6 C L mg−1 m−2) and a broader dynamic range (25 to 800 mg L−1). In conclusion, our study underscores the pivotal role of cathode selection in 3D-printed MFC biosensors, influencing anodic biofilm enrichment time and overall BOD assessment performance. We recommend the use of cost-effective CP GDL with hand-coated CL for short-term MFC biosensor applications, while advocating for CC GDL supplied with CL as the preferred choice for long-term sensing implementations with enduring reliability.

Resilience of anodic biofilm in microbial fuel cell biosensor for BOD monitoring of urban wastewater

Efficient wastewater treatment monitoring is vital for addressing water scarcity. Microbial fuel cells (MFCs) have emerged as real-time biosensors for biochemical oxygen demand (BOD) in urban wastewater. Discrepancies in signal generation may arise due to changes in the composition and metabolism of mixed-culture electroactive biofilms stemming from different wastewater compositions. In this study, 3D-printed MFC-based biosensors were employed to assess the BOD of sterile complex artificial wastewater and untreated urban wastewater. Alterations in the microbial composition of the anode were evaluated using 16S rRNA sequencing and metagenomics analysis. Results show that MFC-based biosensors can be effectively recalibrated for diverse types of wastewater, maintaining consistent sensitivity (0.64 ± 0.10 mA L mg−1 m−2 with synthetic wastewater and 0.78 ± 0.13 mA L mg−1 m−2 with urban wastewater) and limit of detection (49 ± 8 mg L−1 for synthetic wastewater and 44 ± 7 mg L−1 for urban wastewater). Crucially, pre-sterilization, conductivity adjustments, and nitrogen purging of wastewater are not required before its introduction into the biosensor. However, the presence of native aerobic microorganisms in the wastewater might affect the current output. Metagenomics and taxonomic analyses revealed that the alterations in biofilm composition are predominantly in response to the varied chemical and microbiological compositions of different substrates. Despite variations in anodic biofilm composition, the MFC-based biosensor maintains a relative error comparable to the standard BOD test. This highlights the resilience and flexibility of the biosensor when directly used with a variety of wastewater types before full biofilm adjustment.

Low temperature acclimation of electroactive microorganisms may be an effective strategy to enhance the toxicity sensing performance of microbial fuel cell sensors

Microbial fuel cell (MFC) sensing is a promising method for real-time detection of water biotoxicity, however, the low sensing sensitivity limits its application. This study adopted low temperature acclimation as a strategy to enhance the toxicity sensing performance of MFC biosensor. Two types of MFC biosensors were started up at low (10 °C) or warm (25 °C) temperature, denoted as MFC-Ls and MFC-Ws respectively, using Pb2+ as the toxic substance. MFC-Ls exhibited superior sensing sensitivities towards Pb2+ compared with MFC-Ws at both low (10 °C) and warm (25 °C) operation temperatures. For example, the inhibition rate of voltage of MFC-Ls was 22.81 % with 1 mg/L Pb2+ shock at 10 °C, while that of MFC-Ws was only 5.9 %. The morphological observation showed the anode biofilm of MFC-Ls had appropriate amount of extracellular polymer substances, thinner thickness (28.95 μm for MFC-Ls and 41.58 μm for MFC-Ws) and higher proportion of living cells (90.65 % for MFC-Ls and 86.01 % for MFC-Ws) compared to that of MFC-Ws. Microbial analysis indicated the enrichment of psychrophilic electroactive microorganisms and cold-active enzymes as well as their sensitivity to Pb2+ shock was the foundation for the effective operation and good performance of MFC-Ls biosensors. In conclusion, low temperature acclimation of electroactive microorganisms enhanced not only the sensitivity but also the temperature adaptability of MFC biosensors.

Selective Sensing in Microbial Fuel Cell Biosensors: Insights from Toxicity-Adapted and Non-Adapted Biofilms for Pb(II) and Neomycin Sulfate Detection.

This study introduces the utilization of self-powered microbial fuel cell (MFC)-based biosensors for the detection of biotoxicity in wastewater. Current MFC-based biosensors lack specificity in distinguishing between different pollutants. To address this limitation, a novel approach is introduced, capitalizing on the adaptive capabilities of anodic biofilms. By acclimating these biofilms to specific pollutants, an enhancement in the selectivity of MFC biosensors is achieved. Notably, electrochemically active bacteria (EAB) were cultivated on 3D porous carbon felt with and without a model toxicant (target analyte), resulting in the development of toxicant-resistant anodic biofilms. The model toxicants, Pb2+ ions and the antibiotic neomycin sulfate (NS), were deployed at a concentration of 1 mg L-1 during MFC operation. The influence of toxicity on biofilm growth and power production was investigated through polarization and power density curves. Concurrently, the electrochemical activity of both non-adapted and toxicity-adapted biofilms was investigated using cyclic voltammetry. Upon maturation and attainment of peak powers, the MFC reactors were evaluated individually as self-powered biosensors for pollutant detection in fresh wastewater, employing the external resistor (ER) mode. The selected ER, corresponding to the maximum power output, was positioned between the cathode and anode of each MFC, enabling output signal tracking through a data logging system. Subsequent exposure of mature biofilm-based MFC biosensors to various concentrations of the targeted toxicants revealed that non-adapted mature biofilms generated similar current-time profiles for both toxicity models, whereas toxicity-adapted biofilms produced distinctive current-time profiles. Accordingly, these results suggested that merely by adapting the anodic biofilm to the targeted toxicity, distinct and identifiable current-time profiles can be created. Furthermore, these toxicity-adapted and non-adapted biofilms can be employed to selectively detect the pollutant via the differential measurement of electrical signals. This differentiation offers a promising avenue for selective pollutant detection. To the best of our current knowledge, this approach, which harnesses the natural adaptability of biofilms for enhanced sensor selectivity, represents a pioneering effort in the realm of MFC-based biosensing.

Microbial Fuel Cell Biosensor with Capillary Carbon Source Delivery for Real-Time Toxicity Detection.

A microbial fuel cell (MFC) biosensor with an anode as a sensing element is often unreliable at low or significantly fluctuating organic matter concentrations. To remove this limitation, this work demonstrates capillary action-aided carbon source delivery to an anode-sensing MFC biosensor for use in carbon-depleted environments, e.g., potable water. First, different carbon source delivery configurations using several thread types, silk, nylon, cotton, and polyester, are evaluated. Silk thread was determined to be the most suitable material for passive delivery of a 40 g L-1 acetate solution. This carbon source delivery system was then incorporated into the design of an MFC biosensor for real-time detection of toxicity spikes in tap water, providing an organic matter concentration of 56 ± 15 mg L-1. The biosensor was subsequently able to detect spikes of toxicants such as chlorine, formaldehyde, mercury, and cyanobacterial microcystins. The 16S sequencing results demonstrated the proliferation of Desulfatirhabdium (10.7% of the total population), Pelobacter (10.3%), and Geobacter (10.2%) genera. Overall, this work shows that the proposed approach can be used to achieve real-time toxicant detection by MFC biosensors in carbon-depleted environments.

Closed-Loop Microbial Fuel Cell Control System Designed for Online Monitoring of TOC Dynamic Characteristics in Public Swimming Pool.

Total organic carbon (TOC) in the water of public swimming pools (PSPs) must be monitored online for public health. In order to address the shortcomings of conventional microbial fuel cell biosensor (MFC-biosensor), an innovative biosensor with peculiar closed-loop structure was developed for online monitoring of TOC in PSPs. Its design was based on experimental data, model identification, cybernetics, and digital and real-time simulation. The outcomes of the digital simulation demonstrated that the closed-loop MFC control system possesses the desired structure with a pair of dominant complex-conjugate closed-loop poles (−15.47 ± 7.73j), and the real-time simulation showed that its controller output signals can automatically and precisely track the variation in TOC concentration in PSP water with the desired dynamic response performances; for example, mean delay time was 0.06 h, rise time was 0.12 h, peak time was 0.18 h, maximum overshoot was 7.39%, settling time was 0.22 h, and best fit 0.98. The proposed principle and method of the closed-loop MFC-biosensor control system in the article can also be applied for online monitoring of other substances in water, such as heavy metal ions, chemical toxicants, and so forth, and lay a theoretical foundation for MFC-based online monitoring substances in an aquatic environment.

Recent advances in the analytical strategies of microbial biosensor for detection of pollutants

Microbial biosensor which integrates different types of microorganisms, such as bacteria, microalgae, fungi, and virus have become suitable technologies to address limitations of conventional analytical methods. The main applications of biosensors include the detection of environmental pollutants, pathogenic bacteria and compounds related to illness, and food quality. Each type of microorganisms possesses advantages and disadvantages with different mechanisms to detect the analytes of interest. Furthermore, there is an increasing trend in genetic modifications for the development of microbial biosensors due to potential for high-throughput analysis and portability. Many review articles have discussed the applications of microbial biosensor, but many of them focusing only about bacterial-based biosensor although other microbes also possess many advantages. Additionally, reviews on the applications of all microbes as biosensor especially viral and microbial fuel cell biosensors are also still limited. Therefore, this review summarizes all the current applications of bacterial-, microalgal-, fungal-, viral-based biosensor in regard to environmental, food, and medical-related applications. The underlying mechanism of each microbes to detect the analytes are also discussed. Additionally, microbial fuel cell biosensors which have great potential in the future are also discussed. Although many advantageous microbial-based biosensors have been discovered, other areas such as forensic detection, early detection of bacteria or virus species that can lead to pandemics, and others still need further investigation. With that said, microbial-based biosensors have promising potential for vast applications where the biosensing performance of various microorganisms are presented in this review along with future perspectives to resolve problems related on microbial biosensors.

Microbial fuel cell (MFC)-based biosensor for combined heavy metals monitoring and associated bioelectrochemical process

To explore the feasibility and related mechanism of MFC biosensor for wastewater detection under the action of combined heavy metals. Cyclic voltammetry (CV) and scanning electrochemical impedance spectroscopy (EIS) were used to explore the related bioelectrochemical process. The response of the reactor to single/combined heavy metals, low/high heavy metal concentrations, and the differences in ohmic resistance (Rs) and charge transfer resistance (Rct) were investigated using Ni as the core heavy metal and the combined action of Cd, Cu and Zn. The results indicated that there was a linear relationship between the concentration and output voltage of the MFC biosensor under the action of combined heavy metals (R2 = 0.8803–0.973). However, the internal resistance (Rint) of the MFC biosensor under the action of single heavy metal was far less than that of the combined heavy metal group, and the power density (19.849 W m−3) was 4 times that of the combined heavy metal group (3.109–4.589 W m−3). The Rs of the biosensors in the combined heavy metal group were 0.868Ω and 0.860, which were higher than 0.768Ω of the single heavy metal sensor. With the increase of the concentration of heavy metals in the influent, the increase of Rct was more obvious in the combined group, while the Rs in the single group significantly increased (P < 0.05). The results imply that it is possible for MFC biosensors to be used in the detection of actual water polluted by various heavy metals, but the biosensor performance is mainly limited by Rct, which needs to be further improved.

Effective toxicity assessment of synthetic dye in microbial fuel cell biosensor with spinel nanofiber anode

Textile dyes are one of the most commonly found contaminants in wastewater requiring their insitu real-time monitoring and biotreatment. In the present study, two different microbial fuel cells with plain and magnesium ferrite coated stainless steel mesh (PBS/SS and PBS/MF-SS) bioanodes were tested for the simultaneous biosensing and biotreatment of three different concentrations of Ponceau BS dye with mixed microbial community as biological sensing elements. The study revealed the direct correlation of added toxicant and the performance of microbial fuel cell biosensor and observed an almost perfect linear fit for concentration vs. voltage output graph corroborating the potential of microbial fuel cell as a toxicity detector. The cyclic voltammetry confirmed the bioactivity of microbial fuel cell reactor with reference to the unacclimated system. In addition, the cyclic voltammetry analysis of microbial fuel cells at different dye concentration suggested its promising toxicity sensing potential. Electrochemical Impedance Spectroscopy data confirmed that biofouling affected the internal resistances of microbial fuel cells. In addition, the effect of extended run-time (of a year) on the performance of microbial fuel cell was established by comparing the voltage outputs of this study with our previous work. As compared to the previous study, the voltage output for microbial fuel cells with plain and magnesium ferrite coated stainless steel mesh showed a decline by nearly 53% and 41% respectively suggesting the fouling of system. The lesser drop in the performance for microbial fuel cell with modified electrode showed the potential of modified electrode in more efficient electron transfer in the long run. The results conclude that the microbial fuel cell biosensor provides a quick and effective approach for real-time monitoring of hazardous and recalcitrant contaminants such as dyes in environmental samples; nevertheless, fouling of the system is a significant impediment to the long-term practical implementation of microbial fuel cells.

Development of an innovative MFC-biosensor for real-time monitoring of anaerobic digestion for biogas production: Controlled substrate feeding strategy

A microbial fuel cell (MFC) based biosensor was designed to monitor volatile fatty acids (VFAs) in anaerobic digestion (AD) to control substrate feeding. The VFAs concentrations 7–40.83 mM showed a linear relationship with biosensor voltage (18–67 mV) indicating that voltage < 18 mV was due to low organic matter. Likewise, VFAs concentration lower than 7.87 mM resulted in decreased biogas production rate (BPR) and required substrate feeding. In a continuous food waste AD, the biosensor guided feeding produced 558 mL/g VS with the highest biomethane (62.17%), comparing with 344 and 387 mL/g VS produced by conventional 3- and 7-days intervals feeding, respectively. The microbial community was also more stable under the new strategy, where Prevotella and Methanosarcina were ~6-fold and 1.5-fold higher than conventional groups. The developed portable biosensor (~$200) worked effectively during outdoor monitoring of a domestic biogas plant. The VFAs based MFC biosensors can enhance the biogas yield with minimum substrate feeding while maintaining a suitable microbial community.

Experimental and validation with neural network time series model of microbial fuel cell bio-sensor for phenol detection

Phenol is one of the most commonly known chemical compound found as a pollutant in the chemical industrial wastewater. This pollutant has potential threat for human health and environment, as it can be easily absorbed by the skin and the mucous. Here, we prepared dual chambered microbial fuel cell (MFC) sensor for the detection of phenol. Varying concentration of phenol (100 mg/l, 250 mg/l, 500 mg/l, and 1000 mg/l) was applied as a substrate to the MFC and their change in output voltage was also measured. After adding 100 mg/l, 250 mg/l, 500 mg/l, and 1000 mg/l of phenol as sole substrate to the MFC, the maximum voltage output was obtained as 360 ± 10 mV, 395 ± 8 mV, 320 ± 7 mV, 350 ± 5 mV respectively. This biosensor was operated using industrial wastewater isolated microbes as a sensing element and phenol was used as a sole substrate. The topologies of ANN were analyzed to get the best model to predict the power output of MFCs and the training algorithms were compared with their convergence rates in training and test results. Time series model was used for regression analysis to predict the future values based on previously observed values. Two types of mathematical modeling i.e. Scaled Conjugate Gradient (SCG) algorithm and Time-series model was used with 44 experimental data with varying phenol concentration and varying synthetic wastewater concentration to optimize the biosensor performance. Both SCG and time series showing the best results with R2 value 0.98802 and 0.99115.

On-line monitoring of water quality with a floating microbial fuel cell biosensor: field test results

Real-time biomonitoring using microbial fuel cell (MFC) based biosensors have been demonstrated in several laboratory studies, but field validation is lacking. This study describes the long-term performance of an MFC based biosensor developed for real-time monitoring of changes in the water quality of a metal-contaminated stream. After a startup in the laboratory, biosensors were deployed in a stream close to an active mining complex in Sudbury, ON, Canada. Three sites within the stream were selected for biosensors installation based on their positions relative to the mining complex discharge points - upstream (lowest heavy metals concentration), midpoint and downstream. The biosensors installed at these sites were able to detect, in real-time, temporal changes in the water quality over a 2-month period. The biosensor response was confirmed by the results of a conventional toxicity assay (48-h acute Daphnia magna) as well as analytical measurements of heavy metals concentration in the stream. We conclude that the biosensor could detect changes in the overall water quality of the stream despite the uncontrolled situations typical for field operations as compared to laboratory conditions. To further explain the results observed during the field test, the rapid Microtox bioassay and D. magna assay were used to investigate the possible contributions of the two dominant mining metals (Nickel and Copper) to water toxicity in the test area.

Self-powered and reusable microbial fuel cell biosensor for toxicity detection in heavy metal polluted water

The development of efficient and high yield techniques and tools are necessary in the current scenario where clean and pollution free water resource are diminishing. In this work, a self-powered and reusable single chambered cylindrical microbial fuel cell (MFC) was developed for toxicity detection in water containing heavy metal ions. The bio-sensing ability of electroactive microbial consortia isolated from industrial wastewater was investigated towards four model heavy metal contaminants (Copper (Cu2+), Chromium (Cr6+), Zinc (Zn2+) and Nickel (Ni2+)). Their inhibition ratio of 5 mg Cu2+, 10 mg Cu2+, 20 mg Cu2+ was found 5.06%, 31.25%, 78.57%, for 5 mg Cr6+, 10 mg Cr6+, 20 mg Cr6+ was found 6.66%, 80.00%, 93.67% for 5 mg Zn2+, 10 mg Zn2+, 20 mg Zn2+ was found 13.33%, 28.57%, 33.07%, and for 5 mg Ni2+, 10 mg Ni2+, 20 mg Ni2+ was found 6.66%, 18.75%, 23.33% respectively. To examine the reusability of biosensor, Sodium acetate (NaAc) was used as key organic substance. After toxic heavy metals shock the fuel cells are fed with Sodium acetate (NaAc) to investigate their recovery cycle time. After recovery of electroactive microbial consortia, the MFC based biosensor shown sensitive towards the Cu2+, Cr6+, Zn2+, and Ni2+ at concentrations above 10 mgL−1. Our experimental result showing that, this type of biosensor is very feasible and potential application in toxicity detection of heavy metals polluted water. This type biosensor device is very cost effective in situ system for water contaminants detection.

Microbial fuel cell biosensor for the determination of biochemical oxygen demand of wastewater samples containing readily and slowly biodegradable organics

ObjectivesSingle-chamber air cathode microbial fuel cells (MFCs) were applied as biosensors for biochemical oxygen demand (BOD) measurement of real wastewaters with considerable suspended and/or slowly biodegradable organic content.ResultsThe measurement method consists of batch sample injection, continuous measurement of cell voltage and calculation of total charge (Q) gained during the biodegradation of organic content. Diverse samples were analyzed: acetate and peptone samples containing only soluble readily biodegradable substrates; corn starch and milk samples with suspended and colloidal organics; real domestic and brewery wastewaters. Linear regression fitted to the Q vs. BOD5 measurement points of the real wastewaters provided high (> 0.985) R2 values. Time requirement of the measurement varied from 1 to 4 days, depending on the composition of the sample.ConclusionsRelative error of BOD measured in the MFCs comparing with BOD5 was less than 10%, thus the method might be a good basis for the development of on-site automatic BOD sensors for real wastewater samples.

Microbial fuel cell soft sensor for real-time toxicity detection and monitoring.

Real-time toxicity detection and monitoring using a microbial fuel cell (MFC) is often based on observing current or voltage changes. Other methods of obtaining more information on the internal state of the MFC, such as electrochemical impedance spectroscopy (EIS), are invasive, disruptive, time consuming, and may affect long-term MFC performance. This study proposes a soft sensor approach as a non-invasive real-time method for evaluating the internal state of an MFC biosensor during toxicity monitoring. The proposed soft sensor approach is based on estimating the equivalent circuit model (ECM) parameters in real time. A flow-through MFC biosensor was operated at several combinations of carbon source (acetate) and toxicant (copper) concentrations. The ECM parameters, such as internal resistance, capacitance, and open-circuit voltage, were estimated in real time using a numerical parameter estimation procedure. The soft sensor approach proved to be an adequate replacement for EIS measurements in quantifying changes in the biosensor internal parameters. The approach also provided additional information, which could lead to earlier detection of the toxicity onset.

A copper-specific microbial fuel cell biosensor based on riboflavin biosynthesis of engineered Escherichia coli.

Copper pollution poses a serious threat to the aquatic environment; however, in situ analytical methods for copper monitoring are still scarce. In the current study, Escherichia coli Rosetta was genetically modified to express OprF and ribB with promoter Pt7 and PcusC , respectively, which could synthesize porin and senses Cu2+ to produce riboflavin. The cell membrane permeability of this engineered strain was increased and its riboflavin production (1.45-3.56 μM) was positively correlated to Cu2+ (0-0.5 mM). The biosynthetic strain was then employed in microbial fuel cell (MFC) based biosensor. Under optimal operating parameters of pH 7.1 and 37°C, the maximum voltage (248, 295, 333, 352, and 407 mV) of the constructed MFC biosensor showed a linear correlation with Cu2+ concentration (0.1, 0.2, 0.3, 0.4, 0.5 mM, respectively; R2 = 0.977). The continuous mode testing demonstrated that the MFC biosensor specifically senses Cu2+ with calculated detection limit of 28 μM, which conforms to the common Cu2+ safety standard (32 μM). The results obtained with the developed biosensor system were consistent with the existing analytical methods such as colorimetry, flame atomic absorption spectrometry, and inductively coupled plasma optical emission spectrometry. In conclusion, this MFC-based biosensor overcomes the signal conversion and transmission problems of conventional approaches, providing a fast and economic analytical alternative for in situ monitoring of Cu2+ in water.

Hibernations of electroactive bacteria provide insights into the flexible and robust BOD detection using microbial fuel cell-based biosensors

Microbial fuel cell (MFC) biosensors have been suggested as an alternative detection method for biochemical oxygen demand (BOD). However, it is absolutely essential to develop maintenance procedures for MFC biosensors` because in practice the lay-up period cannot be avoided. In this work, setting electroactive bacteria (EAB) under hibernation condition was demonstrated to be a feasible maintenance method, which provided important insights into the flexible and robust BOD detection using MFC biosensors. Standard BOD solution containing 500, 200, and 20 mg/L BOD were used to evaluate the detection performance after EAB hibernations. Results demonstrated quick recovery of voltage output and high-accuracy BOD detection after hibernations up to 30 days in MFC biosensors detecting 500 mg/L and 200 mg/L BOD. Identical anode potentials after the EAB hibernations suggested intact bacterial ability of current generation. Non-turnover cyclic voltammetry immediately collected after the hibernations suggested multiple redox couples and the presence of cytochromes that played key roles in EAB metabolism and functioned as temporary electron sinks during the hibernations, leading to the increased detected BOD concentration in the restarting cycles. Generally, setting EAB under hibernation condition is a simple and convenient maintenance method for MFC-based BOD biosensors, which not only provides insights into flexible and robust BOD detection, but also be helpful for other MFC biosensing instruments.

Impact of heterotrophic denitrification on BOD detection of the nitrate-containing wastewater using microbial fuel cell-based biosensors

Microbial fuel cell (MFC)-based biosensors are promising alternative biochemical oxygen demand (BOD) detection method. However, the presence of alternative electron acceptor such as nitrate will interfere BOD detection because of the heterotrophic denitrification. So, it is essentially important to investigate how nitrate influences BOD detection and to make correction. In this work, standard BOD solution containing 20–500 mg/L BOD was used to evaluate performance of MFC biosensors impacted with 0–50 mg/L NO3−-N. Results demonstrated the underestimated BOD concentration detected using biosensors with impact of nitrate reduction. Graphical and mathematical method was proposed to make correction, and the corrected BOD concentration accurately indexing the organic matter concentration of the nitrate-containing sample could be obtained. Voltage output, polarization curve and cyclic voltammetry collectively suggested that denitrifying bacteria outcompeted over electricity-generating bacteria for electron donors, and that heterotrophic anodic denitrification was the priority process compared to current production. Generally, the more nitrate in standard solution, the more electron donors consumed for nitrate reduction and the less left for current production. The main nitrogen removal processes in MFC biosensors involved heterotrophic denitrification and ammonification at anode, ammonium transport to cathode chamber, and bioelectrochemical autotrophic denitrification at cathode. Phyla Bacteroidetes, Proteobacteria and Firmicutes were the dominant bacteria, accounting for more than 92% of the whole population in the anode chamber, while the phyla Bacteroidetes, Proteobacteria and Actinobacteria accounted for more than 84% in cathode chamber. The findings in this work provide important insights into BOD detection of nitrate-containing wastewater using MFC biosensors.

Influence of wastewater microbial community on the performance of miniaturized microbial fuel cell biosensor

Microbial fuel cells (MFCs) based sensors had been studied in measuring biochemical oxygen demand (BOD) or the equivalent chemical oxygen demand (COD) recently. Limited attention has been paid to the effect of the microbial communities in wastewater on the responses of these sensors. This study systematically evaluated, for the first time, the effect of wastewater samples from a variety of sources on the electrical response of a micro-fabricated double-chamber MFC device. It was found that the response of the MFC is positively correlated with the bacterial composition, in particular electroactive bacteria. The presence of aerobic bacteria in the sample reduces the current generation. These findings indicated that the bacterial content of the water sample could be a significant interference source and must be considered in the use of µMFC-based sensors. Filtering samples may be effective in improving the reliability of these microsensors.