Modeling and optimization strategies towards performance enhancement of microbial fuel cells

Regulating microbial redox reactions towards enhanced removal of refractory organic nitrogen from wastewater

Biotechnology for wastewater treatment is mainstream and effective depending upon microbial redox reactions to eliminate diverse contaminants and ensure aquatic ecological health. However, refractory organic nitrogen compounds (RONCs, e.g., nitro-, azo-, amide-, and N-heterocyclic compounds) with complex structures and high toxicity inhibit microbial metabolic activity and limit the transformation of organic nitrogen to inorganic nitrogen. This will eventually result in non-compliance with nitrogen discharge standards. Numerous efforts suggested that applying exogenous electron donors or acceptors, such as solid electrodes (electrostimulation) and limited oxygen (micro-aeration), could potentially regulate microbial redox reactions and catabolic pathways, and facilitate the biotransformation of RONCs. This review provides comprehensive insights into the microbial regulation mechanisms and applications of electrostimulation and micro-aeration strategies to accelerate the biotransformation of RONCs to organic amine (amination) and inorganic ammonia (ammonification), respectively. Furthermore, a promising approach involving in-situ hybrid anaerobic biological units, coupled with electrostimulation and micro-aeration, is proposed towards engineering applications. Finally, employing cutting-edge methods including multi-omics analysis, data science driven machine learning, technology-economic analysis, and life-cycle assessment would contribute to optimizing the process design and engineering implementation. This review offers a fundamental understanding and inspiration for novel research in the enhanced biotechnology towards RONCs elimination.

Kinetic modeling for miniaturize single-chambered microbial fuel cell: effects of biochemical reaction on its performance

In this study, Nernst growth model equations are used to explain the anodic biofilm (ABF) modeling, linear sweep voltammetry (LSV) at various growth stages of biofilm, and polarization curve modeling for its electron generation behavior in a miniaturized single-chambered microbial fuel cell (SMFC). Kinetic constants of various growth model equations were determined using non-linear regression analysis. Maximum specific growth rate (μmax) at anodic surface is observed 0.016 h-1 at a glucose concentration of 12 g L-1, whereas retardation in μmax is observed 14 g L-1 or more in SMFC. LSV results showed maximum current density of 6720.56 mA m-2. Anode performance in SMFC is examined through polarization curve resulting maximum open-circuit voltage (OCV), minimum charge transfer loss, and ohmic loss for NWG (NiWO4 impregnated on rGO), NiWO4, rGO, and plain CC (carbon cloth) anode. These results demonstrate significant enhancement in performance of MFC to lead towards model-based process controlling for significant scale-up in future.

Spatially-assembled binary carbon anode synergizing directional electron transfer and enriched microbe accommodation for wastewater treatment and energy conversion: From simulation to experiments

Bioelectrochemical systems (BESs) hold prospects in wastewater energy and resource recovery. Anode optimization is important for simultaneous enhancement of wastewater energy conversion and effluent quality in BESs. In this study, a multi-physics model coupling fluid flow, organic degradation and electrochemical process was constructed to guide the design and optimization of BES anodes. Based on the multi-physics simulation, spatially-assembled binary carbon anodes composed of three-dimensional carbon mesh skeleton and granular activated carbon were proposed and established. The granular activated carbon conducive to microbe accommodation played a vital role in improving effluent water quality, while the carbon mesh skeleton favoring electron collection and transfer could enhance the bioelectricity output. With an average chemical oxygen demand (COD) removal rate of 0.442 kg m-3 d-1, a maximum power density of 20.6 W m-3 was achieved in the optimized composite anode BES, which was 25% and 154% higher than carbon mesh skeleton BES and granular activated carbon BES. Electroactive bacteria were enriched in composite anodes and performed important functions related to microbial metabolism and energy production. The spatially-assembled binary carbon anode with low carbon mesh packing density was more cost-effective with a daily energy output per anode cost of 221 J d-1 RMB-1. This study not only provides a cost-efficient alternative anode to simultaneously improve organic degradation and power generation performance, but also demonstrates the potential of multi-physics simulation in offering theoretical support and prediction for BES configuration design as well as optimization.

Development, performance evaluation, and kinetic studies of microbial fuel cell based auto dripping bioelectrochemical reactor (AutoDriBER) for urine treatment

A bioelectrochemical reactor is an assembly, which facilitates energy generation and resource recovery using electrochemically active microorganisms. To maximise energy production from wastewater in this bioreactor system special design is required. Therefore, in the present study, continuous flow auto dripping bioelectrochemical reactors (AutoDriBERs) were developed as a single and multi-electrode assembly for urine treatment. Further, their performance was assessed by connecting reactors in series and parallel arrangements. AutoDriBER configured in series connection showed the highest 93.64 ± 1.57% chemical oxygen demand removal rate with the 1.38 ± 0.64 V voltage and 2.54 W m-3 polarisation power density. The optimum flow rate for maximum voltage production was tested with various models i.e. the linear, exponential, Sweibull-1, and Sweibull-2 models to confirm voltage prediction and its validity. The Linear and exponential models were found best fitted for voltage production with R2 value of 0.999. These findings infer a novel approach toward optimisation of the complex, inexpensive and self-sufficient design for electricity generation from energy-rich urine wastewater in rural areas.

Advances and challenges in biocathode microbial electrolysis cells for chlorinated organic compounds degradation from electroactive perspectives

Microbial electrolysis cell (MEC) is a promising in-situ strategy for chlorinated organic compound (COC) pollution remediation due to its high efficiency, low energy input, and long-term potential. Reductive dechlorination as the most critical step in COC degradation which takes place primarily in the cathode chamber of MECs is a complex biochemical process driven by the behavior of electrons. However, no information is currently available on the internal mechanism of MEC in dechlorination from the perspective of the whole electron transfer procedure and its dependent electrode materials. This review addresses the underlying mechanism of MEC on the fundamental of the generation (electron donor), transmission (transfer pathway), utilization (functional microbiota) and reception (electron acceptor) of electrons in dechlorination. In addition, the vital role of varied cathode materials involved in the entire electron transfer procedure during COC dechlorination is emphasized. Subsequently, suggestions for future research, including model construction, cathode material modification, and expanding the applicability of MECs to removal gaseous COCs have been proposed. This paper enriches the mechanism of COC degradation by MEC, and thus provides the theoretical support for the scale-up bioreactors for efficient COC removal.

Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling

Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R2) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model's low RMSE and high R2 values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 °C, 1.2 M, and 400 mL/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively.

The race between classical microbial fuel cells, sediment-microbial fuel cells, plant-microbial fuel cells, and constructed wetlands-microbial fuel cells: Applications and technology readiness level

Microbial fuel cell (MFC) is an interesting technology capable of converting the chemical energy stored in organics to electricity. It has raised high hopes among researchers and end users as the world continues to face climate change, water, energy, and land crisis. This review aims to discuss the journey of continuously progressing MFC technology from the lab to the field so far. It evaluates the historical development of MFC, and the emergence of different variants of MFC or MFC-associated other technologies such as sediment-microbial fuel cell (S-MFC), plant-microbial fuel cell (P-MFC), and integrated constructed wetlands-microbial fuel cell (CW-MFC). This review has assessed primary applications and challenges to overcome existing limitations for commercialization of these technologies. In addition, it further illustrates the design and potential applications of S-MFC, P-MFC, and CW-MFC. Lastly, the maturity and readiness of MFC, S-MFC, P-MFC, and CW-MFC for real-world implementation were assessed by multicriteria-based assessment. Wastewater treatment efficiency, bioelectricity generation efficiency, energy demand, cost investment, and scale-up potential were mainly considered as key criteria. Other sustainability criteria, such as life cycle and environmental impact assessments were also evaluated.

Customized Multichannel Measurement System for Microbial Fuel Cell Characterization

This work presents the development of an automatic and customized measuring system employing sigma-delta analog-to-digital converters and transimpedance amplifiers for precise measurements of voltage and current signals generated by microbial fuel cells (MFCs). The system can perform multi-step discharge protocols to accurately measure the power output of MFCs, and has been calibrated to ensure high precision and low noise measurements. One of the key features of the proposed measuring system is its ability to conduct long-term measurements with variable time steps. Moreover, it is portable and cost-effective, making it ideal for use in laboratories without sophisticated bench instrumentation. The system is expandable, ranging from 2 to 12 channels by adding dual-channel boards, which allows for testing of multiple MFCs simultaneously. The functionality of the system was tested using a six-channel setup, and the results demonstrated its ability to detect and distinguish current signals from different MFCs with varying output characteristics. The power measurements obtained using the system also allow for the determination of the output resistance of the MFCs being tested. Overall, the developed measuring system is a useful tool for characterizing the performance of MFCs, and can be helpful in the optimization and development of sustainable energy production technologies.

Bioengineering of biowaste to recover bioproducts and bioenergy: A circular economy approach towards sustainable zero-waste environment

The inevitable need for waste valorisation and management has revolutionized the way in which the waste is visualised as a potential biorefinery for various product development rather than offensive trash. Biowaste has emerged as a potential feedstock to produce several value-added products. Bioenergy generation is one of the potential applications originating from the valorisation of biowaste. Bioenergy production requires analysis and optimization of various parameters such as biowaste composition and conversion potential to develop innovative and sustainable technologies for most effective utilization of biowaste with enhanced bioenergy production. In this context, feedstocks, such as food, agriculture, beverage, and municipal solid waste act as promising resources to produce renewable energy. Similarly, the concept of microbial fuel cells employing biowaste has clearly gained research focus in the past few decades. Despite of these potential benefits, the area of bioenergy generation still is in infancy and requires more interdisciplinary research to be sustainable alternatives. This review is aimed at analysing the bioconversion potential of biowaste to renewable energy. The possibility of valorising underutilized biowaste substrates is elaborately presented. In addition, the application and efficiency of microbial fuel cells in utilizing biowaste are described in detail taking into consideration of its great scope. Furthermore, the review addresses the significance bioreactor development for energy production along with major challenges and future prospects in bioenergy production. Based on this review it can be concluded that bioenergy production utilizing biowaste can clearly open new avenues in the field of waste valorisation and energy research. Systematic and strategic developments considering the techno economic feasibilities of this excellent energy generation process will make them a true sustainable alternative for conventional energy sources.

Critical review of biochemical pathways to transformation of waste and biomass into bioenergy

In recent years, biofuel or biogas have become the primary source of bio-energy, providing an alternative to conventionally used energy that can meet the growing energy demand for people all over the world while reducing greenhouse gas emissions. Enzyme hydrolysis in bioethanol production is a critical step in obtaining sugars fermented during the final fermentation process. More efficient enzymes are being researched to provide a more cost-effective technique during enzymatic hydrolysis. The exploitation of microbial catabolic biochemical reactions to produce electric energy can be used for complex renewable biomasses and organic wastes in microbial fuel cells. In hydrolysis methods, a variety of diverse enzyme strategies are used to promote efficient bioethanol production from various lignocellulosic biomasses like agricultural wastes, wood feedstocks, and sea algae. This paper investigates the most recent enzyme hydrolysis pathways, microbial fermentation, microbial fuel cells, and anaerobic digestion in the manufacture of bioethanol/bioenergy from lignocellulose biomass.

Effect of Sodium Lauryl Sulfate on Sorption of Cells of the Electrogenic Bacterium Strain Micrococcus luteus on Carbon Cloth

Results of a study into the effect of anionic surfactant sodium lauryl sulfate on the sorption of cells of the electrogenic bacteria strain Micrococcus luteus 1-I on the surface of carbon cloth used as electrodes in microbial fuel cell (MFC) technology are presented. Investigations using spectrophotometry, microscopy and microbiology revealed an increase in the degree of sorption of microbial cells on carbon cloth under the action of sodium lauryl sulfate at concentrations of 10 and 100 mg/l. The sorption of cells did not significantly differ from the control at a surfactant content of 200, 400 and 800 mg/l. It had no negative effect on bacterial growth in the concentration range from 10 to 800 mg/l. Due to the fairly high resistance of the electrogenic strain M. luteus 1-I to sodium lauryl sulfate, a widespread component of wastewater, it may be considered as a prospective bioagent for the treatment of domestic wastewater using MFC technology.

Artificial intelligence technologies in bioprocess: Opportunities and challenges

Bioprocess control and optimization are crucial for tapping the metabolic potential of microorganisms, and which have made great progress in the past decades. Combination of the current control and optimization technologies with the latest computer-based strategies will be a worth expecting way to improve bioprocess further. Recently, artificial intelligence (AI) emerged as a data-driven technique independent of the complex interactions used in mathematical models and has been gradually applied in bioprocess. In this review, firstly, AI-guided modeling approaches of bioprocess are discussed, which are widely applied to optimize critical process parameters (CPPs). Then, AI-assisted rapid detection and monitoring technologies employed in bioprocess are summarized. Next, control strategies according to the above two technologies in bioprocess are analyzed. Lastly, current research gaps and future perspectives on AI-guided optimization and control technologies are discussed. This review provides theoretical guidance for developing AI-guided bioprocess optimization and control technologies.

A mathematical model of catalyst combination design and temperature control in the preparation of C4 olefins through ethanol coupling

The preparation of C₄ olefins through ethanol catalytic coupling is a crucial area of study. According to the experimental data obtained by a chemical laboratory for different catalysts at different temperatures, three mathematical models were developed to provide insights into the relationships among ethanol conversion rate, C₄ olefins selectivity, yield, catalyst combination, and temperature. The first model is a nonlinear fitting function that analyses the relationships among ethanol conversion rate, C₄ olefins selectivity, and temperature under varying catalyst combinations. Two-factor analysis of variance was employed to determine the influence of catalyst combinations and temperatures on ethanol conversion rate and C₄ olefins selectivity. The second model is a multivariate nonlinear regression model that describes the relationships among the yield of C₄ olefins, catalyst combination, and temperature. Finally, an optimization model was derived based on the experimental conditions; it provides a solution for the selection of the optimal catalyst combinations and temperatures to achieve the maximum yield of C₄ olefins. This work has significant implications for the field of chemistry and the production of C₄ olefins.

The preparation of C₄ olefins through ethanol catalytic coupling is a crucial area of study.

Scale-up of the bioelectrochemical system: Strategic perspectives and normalization of performance indices

Electrochemists and ecological engineers find environmental bioelectrochemistry appealing; however, there is a big gap between expectations and actual progress in bioelectrochemical system (BES). Implementing such technology opens new opportunities for novel electrochemical reactions for resource recovery and effective wastewater treatment. Loopholes of BES exist in its scaling-up applications, and numerous attempts toward practical applications (200, 1000, and 1500 L) are key successive indicators toward its commercialization. This review emphasized the critical rethinking of standardization of performance indices i.e. current generation (A/m²), net energy recovery (kWh/kg·COD), product/resource yield (mM), and economic feasibility ($/kWh) to make fair comparison with the existing treatment system. Therefore, directional perspectives, including modularity, energy-cost balance, energy and resource recovery, have been proposed for the sustainable market of BES. The current state of the art and up-gradation in resource recovery and contaminant removal warrants a systematic rethinking of functional worth and niches of BES for practical applications.

Increase in Electrical Parameters Using Sucrose in Tomato Waste

The use of organic waste as fuel for energy generation will reduce the great environmental problems currently caused by the consumption of fossil sources, giving agribusiness companies a profitable way to use their waste. In this research, tomato waste with different percentages of sucrose (0-target, 5, 10, and 20%) was used in microbial fuel cells manufactured on a laboratory scale with zinc and copper electrodes, managing to generate maximum peaks of voltage and a current of 1.08 V and 6.67 mA in the cell with 20% sucrose, in which it was observed that the optimum operating pH was 5.29, while the MFC with 0% (target) sucrose generated 0.91 V and 3.12 A on day 13 with a similar pH, even though all the cells worked in an acidic pH. Likewise, the cell with 20% sucrose had the lowest internal resistance (0.148541 ± 0.012361 KΩ) and the highest power density (224.77 mW/cm2) at a current density of 4.43 mA/cm2, while the MFC with 0% sucrose generated 160.52 mW/cm2 and 4.38 mA/cm2 of power density and current density, respectively, with an internal resistance of 0.34116 ± 0.2914 KΩ. In this sense, the FTIR (Fourier-transform infrared spectroscopy) of all the substrates used showed a high content of phenolic compounds and carboxylate acids. Finally, the MFCs were connected in a series and managed to generate a voltage of 3.43 V, enough to light an LED (green). These results give great hope to companies and society that, in the near future, this technology can be taken to a larger scale.

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.

Data-driven and validated dimensional analysis for rational scale-up of a dual-chamber microbial fuel cell system for water-energy nexus exploitation

Mathematical modelling of microbial fuel cells (MFC) facilitates their scale-up by maintaining dimensionless parameters across reactor volumes for consistent performance. This study developed data-driven correlations to predict areal power density for a batch-fed dual-chamber MFC using hybridised first-principle mechanistic model and Buckingham's Pi theorem. The established correlations were validated using experimentally-derived data for pre-enriched electroactive biofilm from mixed cultures. The biochemical model parameters are infilled with stoichiometric and thermodynamics estimations. Results showed that the correlations using logistic kinetics (Nash-Sutcliffe Efficiency, NSE = 0.59) outperformed Monod kinetics (NSE = 0.52) as the latter was not suitable for representing the first-order biochemical kinetics under limited substrate conditions. Sensitivity analysis on varying pH and bicarbonate concentration improved model predictions by ± 50%, though relative absolute error was ± 20% due to inherent error of estimated biochemical parameters. The application of hybridised approach for modelling MFC provides renewed perspectives for their rational design and scale-up applications.

General Method for Synthesizing Effective and Durable Electrocatalysts Derived from Cellulose for Microbial Fuel Cells

Microbial fuel cells (MFCs) can be capable of both wastewater treatment and electricity generation, which necessarily depends on the increasing cathodic performances and stability at low cost to realize industrialization. Herein, cellulose, a commercially available and sustainable material, was oxidized as a carbon precursor to produce the oxygen species synergizing the nitrogen-doped carbon (CON-900) catalyst by a facile in situ nitrogen doping method. The incorporation of nitrogen and oxygen with a high content creates more active centers. Meanwhile, the hierarchical porosity of CON-900 contributes to a high specific surface area (652 m² g^-1) and the exposure of accessible active sites. As expected, CON-900 exhibits considerable activity for the oxygen reduction reaction, excellent operating stability, and high poisoning resistance. In addition, the MFC fabricated with CON-900 as a cathode catalyst demonstrates a maximum power density of 1014 ± 23 mW m^-2, which is comparable with that of the Pt/C cathode (1062 ± 14 mW m^-2). This work offers a facile and versatile strategy for various biomass materials to develop low-cost and high-efficiency carbon-based catalysts for MFCs and beyond.

A scalable model of fluid flow, substrate removal and current production in microbial fuel cells

Mathematical modelling can reduce the cost and time required to design complex systems, and is being increasingly used in microbial electrochemical technologies (METs). To be of value such models must be complex enough to reproduce important behaviour of MET, yet simple enough to provide insight into underlying causes of this behaviour. Ideally, models must also be scalable to future industrial applications, rather than limited to describing existing laboratory experiments. We present a scalable model for simulating both fluid flow and bioelectrochemical processes in microbial fuel cells (MFCs), benchmarking against an experimental pilot-scale bioreactor. The model describes substrate transport through a two-dimensional fluid domain, and biofilm growth on anode surfaces. Electron transfer is achieved by an intracellular redox mediator. We find significant spatial variations in both substrate concentration and current density. Simple changes to the reactor layout can greatly improve the overall efficiency, measured in terms of substrate removal and total current generated.

A 2D Modelling Approach for Predicting the Response of a Two-Chamber Microbial Fuel Cell to Substrate Concentration and Electrolyte Conductivity Changes

Bioelectrochemical systems have been the focus of extensive research due to their unique advantages of converting the chemical energy stored in waste to electricity. To acquire a better understanding and optimize these systems, modelling has been employed. A 2D microbial fuel cell (MFC) model was developed using the finite element software Comsol Multiphysics® (version 5.2), simulating a two-chamber MFC operating in batch mode. By solving mass and charge balance equations along with Monod–Butler–Volmer kinetics, the operation of the MFC was simulated. The model accurately describes voltage output and substrate consumption in the MFC. The computational results were compared with experimental data, thus validating the model. The voltage output and substrate consumption originating from the model were in agreement with the experimental data for two different cases (100 Ω, 1000 Ω external resistances). A polarization curve was extracted from the model by shifting the external resistance gradually, calculating a similar maximum power (47 mW/m2) to the observed experimental one (49 mW/m2). The validated model was used to predict the MFC response to varying initial substrate concentrations (0.125–4 g COD/L) and electrolyte conductivity (0.04–100 S/m) in order to determine the optimum operating conditions.

Regulation and augmentation of anaerobic digestion processes via the use of bioelectrochemical systems

Anaerobic digestion (AD) is a biological process that can be used to treat a wide range of carbon-rich wastes and producerenewable, green energy. To maximize energy recovery from various resources while controlling inhibitory chemicals, notwithstanding AD's efficiency, many limitations must be addressed. As a result, bioelectrochemical systems (BESs) have emerged as a hybrid technology, extensively studied to remediate AD inhibitory chemicals, increase AD operating efficacy, and make the process economically viable via integration approaches. Biogas and residual intermediatory metabolites such as volatile fatty acids are upgraded to value-added chemicals and fuels with the help of the BES as a pre-treatment step, within AD or after the AD process. It may also be used directly to generate power. To overcome the constraints of AD in lab-scale applications, this article summarizes BES technology and operations and endorses ways to scale up BES-AD systems in the future.

Scalability of microbial electrochemical technologies: Applications and challenges

During wastewater treatment, microbial electrochemical technologies (METs) are a promising means for in situ energy harvesting and resource recovery. The primary constraint for such systems is scaling them up from the laboratory to practical applications. Currently, most research (∼90%) has been limited to benchtop models because of bioelectrochemical, economic, and engineering design limitations. Field trials, i.e., 1.5 m³ bioelectric toilet, 1000 L microbial electrolysis cell and industrial applications of METs have been conducted, and their results serve as positive indicators of their readiness for practical applications. Multiple startup companies have invested in the pilot-scale demonstrations of METs for industrial effluent treatment. Recently, advances in membrane/electrode modification, understanding of microbe-electrode interaction, and feasibility of electrochemical redox reactions have provided new directions for realizing the practical application. This study reviews the scaling-up challenges, success stories for onsite use, and readiness level of METs for commercialization that is inexpensive and sustainable.

Optimum dose of Chaetoceros for controlling methanogenesis to improve power production of microbial fuel cell

The marine algae Chaetoceros contains hexadecatrienoic acid, which suppresses methanogen development and improves the coulombic efficiency (CE) of microbial fuel cells (MFC). To inhibit the methanogens, optimum concentration of marine algae should be added to the anaerobic sludge to enhance the performance of MFC. A varying concentration of Chaetoceros ranging from 1 to 20 mg/mL was carried out for pretreatment of an anaerobic-mix consortium to suppress methanogens. MFC inoculated with pretreated anaerobic sludge with 10 mg/mL Chaetoceros showed a maximum power density of 21.62 W/m³ and a maximum CE of 37.25%, which was considerably higher than the treatment with other concentrations. At 10 mg/mL concentration, Tafel analysis of the anode in the MFC showed a higher exchange current density of 66.35 mA/m² and a lower charge transfer resistance of 0.97 Ω.m², revealing higher bio-electrochemical activity. The performance of MFC improved when the concentration of Chaetoceros was increased up to 10 mg/mL, but then began to decline as the concentration increased further. Thus, the optimum dose of Chaetoceros to be added in the mix-anaerobic consortium to optimize the power performance of MFC was determined, which can be carried out in scaled-up MFCs.

Fungal-mediated electrochemical system: Prospects, applications and challenges

Microbial fuel cells (MFCs) that generate bioelectricity from biodegradable waste have received considerable attention from biologists. Fungi play a significant role as both anodic and cathodic catalysts in MFCs. Saccharomyces cerevisiae is a fungus with an ability to transfer electrons through mediators such as methylene blue (MB), neutral red (NR) or even without a mediator. This unique role of fungal cells in exocellular electron transfer (EET) and their interactions with electrodes hold a lot of promise in areas such as wastewater treatment where yeast cell-based MFCs can be used. The present article highlights the physico-chemical factors affecting the performance of fungal-mediated MFCs in terms of power output and degradation of organic pollutants, along with the challenges associated with fungal MFCs. In addition, to this comparative assessment of fungal-mediated bio-electrochemical systems, their development, possible applications and potential challenges are also discussed.

Effectiveness of constructed wetland integrated with microbial fuel cell for domestic wastewater treatment and to facilitate power generation

Constructed wetlands (CWs) have gained a lot of attention for wastewater treatment due to robustness and natural pollutant mitigation characteristics. This widely acknowledged technology possesses enough merits to derive direct electricity in collaboration with microbial fuel cell (MFC), thus taking advantage of microbial metabolic activities in the anoxic zone of CWs. In the present study, two identical lab-scale CWs were selected, each having 56 L capacity. One of the CW integrated with MFC (CW-MFC) contains two pairs of electrodes, i.e., carbon felt and graphite plate. The first pair of CW-MFC consists of a carbon felt cathode with a graphite plate anode, and the second pair contains a graphite plate cathode with a carbon felt anode. The other CW was not integrated with MFC and operated as a traditional CW for evaluating the performance. CW-MFC and CW were operated in continuous up-flow mode with a hydraulic retention time of 3 days and at different organic loading rates (OLRs) per unit surface area, such as 1.45 g m^-2 day^-1 (OLR-1), 2.43 g m^-2 day^-1 (OLR-2), and 7.25 g m^-2 day^-1 (OLR-3). The CW-MFC was able to reduce the organic matter, phosphate, and total nitrogen by 92%, 93%, and 70%, respectively, at OLR of 1.45 g m^-2 day^-1, which was found to be higher than that obtained in conventional CW. With increase in electrochemical redox activities, the second pair of electrodes made way for 3 times higher power density of 16.33 mW m^-2 as compared to the first pair of electrodes in CW-MFC (5.35 mW m^-2), asserting carbon felt as a good anode material to be used in CW-MFC. The CW-MFC with carbon felt as an anode material is proposed to improve the electro-kinetic activities for scalable applications to achieve efficient domestic wastewater treatment and electricity production.

Production of biofuels from biomass: Predicting the energy employing artificial intelligence modelling

Bioenergy may be a major replacement of fossil fuels which can make the path easier for sustainable development and decrease the dependency on conventional sources of energy. The main concern with the bioenergy is the availability of feedstock, dealing with its economics as well as its demand and supply chain management. This review deals with the finding of distinct potential of different Artificial Intelligence technologies focusing the challenges in bioenergy production system and its overall improvement in application. The study also highlights the contribution of Artificial Intelligence techniques for the prediction of energy from biomass and evaluates the computing-reasoning techniques for managing bioenergy production, biomass supply chain and optimization of process parameters for efficient bioconversion technologies.

Effect of cathodic culture on wastewater treatment and power generation in a photosynthetic sediment microbial fuel cell (SMFC): Canna indica v/s Chlorella vulgaris

The aim of this work was to compare the performance of the two types of photosynthetic microbial fuel cells (MFCs) fed with real wastewater- one having plant Canna indica (PMFC) and the other having alga Chlorella vulgaris (AMFC) at the cathode. The chemical oxygen demand (COD), phosphate, and nitrate removal stood at 57.16% 88.81%, 59.82% for PMFC and 65.27%, 95.59%, 66.61% for the AMFC. While AMFC was slightly superior in water treatment, the power output was 6 times higher in PMFC (22.76 mW m^-2) than the AMFC (3.64 mW m^-2). The biomass growth was good in both systems, with biomass productivity of 0.031 Kg m^-3 day^-1 in AMFC and a leaf area index of 0.006 in PMFC. The study's findings suggest that PMFCs are equally good or even better than AMFCs when the goal is simultaneous water treatment and power generation.

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.

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.

Neural Networks Predicting Microbial Fuel Cells Output for Soft Robotics Applications

The development of biodegradable soft robotics requires an appropriate eco-friendly source of energy. The use of Microbial Fuel Cells (MFCs) is suggested as they can be designed completely from soft materials with little or no negative effects to the environment. Nonetheless, their responsiveness and functionality is not strictly defined as in other conventional technologies, i.e. lithium batteries. Consequently, the use of artificial intelligence methods in their control techniques is highly recommended. The use of neural networks, namely a nonlinear autoregressive network with exogenous inputs was employed to predict the electrical output of an MFC, given its previous outputs and feeding volumes. Thus, predicting MFC outputs as a time series, enables accurate determination of feeding intervals and quantities required for sustenance that can be incorporated in the behavioural repertoire of a soft robot.

Blending of microbial inocula: An effective strategy for performance enhancement of clayware Biophotovoltaics microbial fuel cells

Performance of clayware Biophotovoltaics (BPVs) with three variants of inocula namely anoxygenic photosynthetic bacteria (APB) rich Effective microbes (EM), Up-flow anaerobic sludge blanket reactor (UASB) sludge, SUPER-MIX the blend of EM and UASB inoculum were evaluated on the basis of electrical output and pollutant removal. SUPER-MIX inocula with microbial community comprising of 28.42% APB and 71.58% of other microbes resulted in peak power density of 275 mW/m², 69.3 ± 1.74% Coulombic efficiency and 91 ± 3.96% organic matter removal. The higher performance of the SUPER-MIX than EM and UASB inocula was due to the syntrophic associations of the various APBs and other heterogenous microorganisms in perfect blend which improved biocatalytic electron transfer, electro-kinetic activities with higher redox current and bio-capacitance. The promising performance of clayware BPVs with SUPER-MIX inocula indicate the possibility of BPVs to move towards the scale-up process to minimize the investment towards pure culture by effective blending strategies of inocula.