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Microbial Fuel Cells: Innovations and Applications

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: 15 January 2027 | Viewed by 756

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Guest Editor
Department of Civil and Environmental Engineering, Idaho State University, Pocatello, ID 83209, USA
Interests: microbial fuel cells; resource recovery from wastes; water and wastewater treatment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microbial fuel cells (MFCs) are a promising and sustainable bioelectrochemical technology that leverages the metabolic activity of microorganisms to directly convert organic matter into electricity. This capability allows MFCs to perform critical environmental functions—such as degrading pollutants, removing heavy metals, and recovering valuable nutrients—while simultaneously generating renewable energy.

While traditional research has focused on wastewater treatment and power generation, the scope of MFCs has expanded into a versatile interdisciplinary platform. Innovations now include enzyme-based MFCs, photosynthetic and algae-assisted systems, constructed wetland-MFCs, hydroponic integrations, and microbial desalination cells. Beyond energy and resource recovery, MFCs are also advancing as sensitive tools for environmental biosensing and medical diagnostics.

Nevertheless, transitioning from laboratory-scale innovation to real-world application faces persistent challenges. These include low power density, limitations in electron transfer efficiency, material stability issues such as biofouling and catalyst durability, and high initial costs. Overcoming these barriers requires advances in materials, design, system integration, and scalable implementation.

This Special Issue aims to gather cutting-edge research that addresses these challenges and drives the field forward. We invite original research and review articles focused on novel materials, inventive reactor configurations, performance optimization, and scalable applications. Submissions that apply AI-assisted modeling, machine learning, and data-driven analysis are particularly encouraged, as they hold significant potential for accelerating development and deployment.

We welcome contributions across a broad range of topics including, but not limited to, the following:

  • Genetic engineering, synthetic biology, and microbial consortia design for enhanced electroactivity.
  • Advanced nanomaterials (e.g., graphene, carbon nanotubes) for electrodes, membranes, and catalysts.
  • Novel designs and modifications of MFC components.
  • Innovative reactor architectures and system configurations.
  • Multipurpose applications in wastewater treatment, bioremediation, biosensing, agriculture, and desalination.
  • Scaling-up strategies, techno-economic analysis, and life-cycle assessment.
  • Modeling, simulation, and computational optimization of MFC systems.
  • Field trials, pilot-scale studies, and real-world case studies.

We look forward to your valuable submissions.

Prof. Dr. Chikashi Sato
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microbial fuel cells
  • advanced materials
  • novel designs
  • optimization
  • genetic engineering
  • case studies
  • field trials
  • AI
  • machine learning

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Published Papers (1 paper)

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Research

43 pages, 13720 KB  
Article
Integrated Reactor-State Descriptors for Predicting Electrical Output in Kefir-Derived Microbial Fuel Cells
by Samuel Valle-Asan, Carlos Bastidas-Sánchez, Martin Villalva-Vera, Gustavo Vaca-Triviño and Miguel Ángel Reinoso
Energies 2026, 19(13), 3156; https://doi.org/10.3390/en19133156 - 3 Jul 2026
Viewed by 392
Abstract
Salt-bridge kefir-derived microbial fuel cells (MFCs) provide a low-cost platform for studying fermentation-linked electrical output, but their behavior is often evaluated through isolated current or voltage traces rather than integrated reactor-state evidence. This study assessed laboratory-scale double-chamber MFCs operated under fed-batch conditions with [...] Read more.
Salt-bridge kefir-derived microbial fuel cells (MFCs) provide a low-cost platform for studying fermentation-linked electrical output, but their behavior is often evaluated through isolated current or voltage traces rather than integrated reactor-state evidence. This study assessed laboratory-scale double-chamber MFCs operated under fed-batch conditions with a kefir-derived mixed consortium and molasses-based substrate. Thirty-three independent reactors, including graphite- and graphene-anode configurations, were monitored from day 0 to day 20, generating 693 reactor-day observations. Electrical, redox, temperature, substrate-related, UV–Vis soluble-phase, baseline sequencing, endpoint SEM, FTIR functional-group evidence, and semimechanistic descriptors were integrated to diagnose reactor evolution and predict fixed-condition current output. Current declined from 0.8985 to 0.1133 mA, residual glucose-equivalent decreased from 5.3124 to 0.0127 g L−1, and the glucose-consumption fraction reached 0.9977. Fixed-condition apparent power decreased from 0.8636 to 0.0856 mW, while cumulative charge and cumulative apparent energy averaged 595.02 C and 456.69 J per reactor. FTIR bands supported carbohydrate/EPS, organic-acid, and proteinaceous-matrix signatures consistent with a fermentation–redox–biofilm cascade. The random-forest model showed strong grouped cross-validation performance (R2 = 0.956, RMSE = 0.082 mA, MAE = 0.060 mA, slope = 1.009, r = 0.978). This work supports state-aware current and fixed-condition power-output prediction in kefir-driven MFCs without claiming maximum power-density or complete electrochemical characterization. Full article
(This article belongs to the Special Issue Microbial Fuel Cells: Innovations and Applications)
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