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A 1D mathematical model for a microbial fuel cell

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  • Oliveira, V.B.
  • Simões, M.
  • Melo, L.F.
  • Pinto, A.M.F.R.

Abstract

MFCs (microbial fuel cells) are a promising sustainable technology to meet increasing energy needs, especially using wastewaters as substrates, since they can generate electricity and accomplish wastewater treatment simultaneously. The MFC is a complex system involving bio-electrochemical processes, charge, mass and energy transfer. In this work, a steady state, one-dimensional model accounting for coupled heat, charge and mass transfer, and biofilm formation, along with the electrochemical reactions occurring in the MFC, similar to the ones developed for chemical fuel cells, is presented. The model predicts the correct trends for the influence of current density on the cell voltage, as well as, the influence of substrate concentration and temperature on the MFC performance and biofilm thickness. The model outputs are the temperature and concentration profiles and the biofilm thickness. The proposed model is rapidly and easily implemented and is therefore suitable for inclusion in real-time system level MFC calculations.

Suggested Citation

  • Oliveira, V.B. & Simões, M. & Melo, L.F. & Pinto, A.M.F.R., 2013. "A 1D mathematical model for a microbial fuel cell," Energy, Elsevier, vol. 61(C), pages 463-471.
    • Handle: RePEc:eee:energy:v:61:y:2013:i:c:p:463-471
    DOI: 10.1016/j.energy.2013.08.055
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    1. Sona Kazemi & Melissa Barazandegan & Madjid Mohseni & Khalid Fatih, 2016. "Systematic Study of Separators in Air-Breathing Flat-Plate Microbial Fuel Cells—Part 2: Numerical Modeling," Energies, MDPI, vol. 9(2), pages 1-16, January.
    2. Ortiz-Martínez, V.M. & Salar-García, M.J. & Touati, K. & Hernández-Fernández, F.J. & de los Ríos, A.P. & Belhoucine, F. & Berrabbah, A. Alioua, 2016. "Assessment of spinel-type mixed valence Cu/Co and Ni/Co-based oxides for power production in single-chamber microbial fuel cells," Energy, Elsevier, vol. 113(C), pages 1241-1249.
    3. Tafaoli-Masoule, M. & Bahrami, A. & Elsayed, E.M., 2014. "Optimum design parameters and operating condition for maximum power of a direct methanol fuel cell using analytical model and genetic algorithm," Energy, Elsevier, vol. 70(C), pages 643-652.
    4. Violetta Vasilenko & Irina Arkadeva & Vera Bogdanovskaya & George Sudarev & Sergei Kalenov & Marco Vocciante & Eleonora Koltsova, 2020. "Glucose-Oxygen Biofuel Cell with Biotic and Abiotic Catalysts: Experimental Research and Mathematical Modeling," Energies, MDPI, vol. 13(21), pages 1-21, October.
    5. Chen, Yingwen & Xu, Yuan & Chen, Liuliu & Li, Peiwen & Zhu, Shemin & Shen, Shubao, 2015. "Microbial electrolysis cells with polyaniline/multi-walled carbon nanotube-modified biocathodes," Energy, Elsevier, vol. 88(C), pages 377-384.
    6. Theofilos Kamperidis & Asimina Tremouli & Antonis Peppas & Gerasimos Lyberatos, 2022. "A 2D Modelling Approach for Predicting the Response of a Two-Chamber Microbial Fuel Cell to Substrate Concentration and Electrolyte Conductivity Changes," Energies, MDPI, vol. 15(4), pages 1-15, February.
    7. Ismail, Zainab Z. & Habeeb, Ali A., 2017. "Experimental and modeling study of simultaneous power generation and pharmaceutical wastewater treatment in microbial fuel cell based on mobilized biofilm bearers," Renewable Energy, Elsevier, vol. 101(C), pages 1256-1265.
    8. Ortiz-Martínez, V.M. & Salar-García, M.J. & Hernández-Fernández, F.J. & de los Ríos, A.P., 2015. "Development and characterization of a new embedded ionic liquid based membrane-cathode assembly for its application in single chamber microbial fuel cells," Energy, Elsevier, vol. 93(P2), pages 1748-1757.
    9. Fang, Shuo & Zhang, Yufeng & Zou, Yuezhang & Sang, Shengtian & Liu, Xiaowei, 2017. "Structural design and analysis of a passive DMFC supplied with concentrated methanol solution," Energy, Elsevier, vol. 128(C), pages 50-61.
    10. Hidalgo, Diana & Tommasi, Tonia & Cauda, Valentina & Porro, Samuele & Chiodoni, Angelica & Bejtka, Katarzyna & Ruggeri, Bernardo, 2014. "Streamlining of commercial Berl saddles: A new material to improve the performance of microbial fuel cells," Energy, Elsevier, vol. 71(C), pages 615-623.
    11. Garg, A. & Lam, Jasmine Siu Lee, 2017. "Design of explicit models for estimating efficiency characteristics of microbial fuel cells," Energy, Elsevier, vol. 134(C), pages 136-156.
    12. Fang, Shuo & Zhang, Yufeng & Ma, Zezhong & Sang, Shengtian & Liu, Xiaowei, 2016. "Systemic modeling and analysis of DMFC stack for behavior prediction in system-level application," Energy, Elsevier, vol. 112(C), pages 1015-1023.

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