Comparison between conventional and modified microbial fuel cell for wastewater treatment and electricity generation

Ali, Ahmed Hassoon; Al-Mussawy, H. A.; Hussein, Mohammed Jabbar; Hamadi, N. J.

doi:10.1007/s13762-019-02355-x

Cited by 11 publications

(5 citation statements)

References 21 publications

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“…Some models treat the MFC as a black box, considering only the input and output characteristics of the system, while others are more or less detailed in regard to the processes occurring within the researched system. The mathematical models of the first type comprise those exploiting the approaches of electrochemical impedance spectroscopy [27], artificial neural networks [28,29], Tafel equations [30], etc. For example, in the study [31] on the effect of hydrodynamic mode on the output characteristics aimed to determine dead zones that reduce the effective volume of the reactor, hydrodynamics was shown to affect only the output characteristics of the cathode.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…The voltage of MFCs was predicted using ANN models and compared with experimental results. [13] 3 ANN was used to model 33 MFCs, including 8 substrates and 3 wastewaters. [14] 4 ANN was used to simulate polarization curves with various membrane materials and electrode configurations.…”

Section: Item Descriptionmentioning

confidence: 99%

“…Using an ANFIS model, Ghasemi et al [12] predicted COD removal and power density, then optimized both these parameters using single-object optimization and multi-object optimization. ANN models were used to predict the voltage of MFCs and compared with experimental results by Ahmed et al [13]. A correlation coefficient of 0.999 was obtained for the constructed ANN model.…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Improving Microbial Fuel Cell Performance Using Artificial Intelligence

2023

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Microbial fuel cells have recently received considerable attention as a potential source of renewable energy. Due to its complex and hybrid nature, it has significant nonlinear features and substantial hysteresis behavior, making it hard to optimize and control its power generation directly. This study modeled power density and COD removal using random forest regression and gradient boost regression trees. System inputs are three key parameters that affect performance and commercialization. There is a range of 0.1–0.5 mg/cm2 of Pt, a degree of sulfonation of sulfonated polyether-etherketone varying from 20% to 80%, and a cathode aeration rate of 10–150 mL/min. Based on the model’s accuracies, gradient boost regression was selected for power density prediction and random forest for COD removal prediction. Particle swarm optimization was used as the optimization algorithm after selecting the best models to maximize COD removal and power density. It was found that DS was the most critical parameter for COD removal, and Pt was the most critical parameter for power density. There is a different optimal input value for each model. In order to maximize power density, DS (%) must be 67.7087, Pt (mg/cm2) must be 0.3943, and Aeration (mL/min) must be 117.7192. To maximize COD removal, the DS (%) must be 75.8816, the Pt (mg/cm2) must be 0.3322, and the Aeration (mL/min) must be 75.1933.

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“…Additionally, by adsorbing heavy metals onto GAC via a variety of procedures (van der Waals bonding, ion exchange, chemical bonds, etc. ), the effluent water quality would be improved [17].…”

Section: Optical Electronic and Special Materialsmentioning

confidence: 99%

Investigating the Performance of Single Chamber Microbial Fuel Cell (SCMFC) as Sustainable- Innovative Technique for Electricity Generation and Wastewater Treatment

Adnan,

Hassoon Ali

2023

DDF

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Microbial fuel cells (MFCs) are considered as an economical and sustainable technology for various applications. This study has designed four single-chamber SCMFCs that composed of graphite plates as electrodes and used wastewater as a substrate for microorganisms. In order to evaluate the performance of SCMFC, the experiments were executed in a batch mode over 18 days at various types of salt bridge. Four salt bridges are used namely (KCl, NaCl, KNO3, and Cotton Rope). It was found that KCl generated a maximum voltage of 989 mv. The following results were obtained for wastewater investigated parameters: COD = 94%, PO4 = 88.4%, NO3 = 88%, TSS = 80%, and Fe = 76%, respectively at 1 M KCl. The experiment was then carried out using different values of KCl (1, 1.5, 2, 3 M). It was found that at a molar concentration of 1.5, 1422 mv of maximum voltage has been generated. Results for wastewater treatment demonstrated that COD of 81%, PO4 of 78.2%, NO3 of 79%, TSS of 80%, and Fe of 84%.

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Comparison between conventional and modified microbial fuel cell for wastewater treatment and electricity generation

Cited by 11 publications

References 21 publications

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

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

A New Approach for Improving Microbial Fuel Cell Performance Using Artificial Intelligence

Investigating the Performance of Single Chamber Microbial Fuel Cell (SCMFC) as Sustainable- Innovative Technique for Electricity Generation and Wastewater Treatment

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