4.7 Article Proceedings Paper

Electricity generation in a microbial fuel cell with textile carbon fibre anodes

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.camwa.2019.11.019

关键词

Computational Fluid Dynamics; CFD; Ansys Fluent; 3D bioanode geometry; Microbial fuel cell; Textile carbon fibre electrode

资金

  1. German Ministry of Education and Research (Bundesministerium fur Bildung und Forschung, BMBF) [031B0087D, 031B0087A, 031B0087C]

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This paper discusses the extension of a commercial CFD code to simulate an anode in a Microbial Fuel Cell, and explores the impact of different textile carbon fibre based anode configurations on the electrical performance. The results show that the size of the outer surface of the biofilm determines the quantity of the electrical power delivered by the biofilm.
Commercial Computational Fluid Dynamics (CFD) codes offer a great flexibility to model complex 3D geometries. They have many physical models on board, nevertheless reactions in a Microbial Fuel Cell (MFC) are not included. In this paper, we discuss the extension of Ansys Fluent commercial CFD code to simulate a model of an anode in a Microbial Fuel Cell. The biofilm around the anode is a mixed culture dominated by Geobacter sulfurreducens and is treated as a conductive material. Besides the stationary 3D Navier-Stokes equation for fluid flow and the species balance equation for acetate in the water and in the biofilm, the model includes a model for the species mass fraction of acetate at the boundary between water and biofilm. Furthermore, we added a sink for acetate as well as a source for electrons and a stationary electric potential equation in the biofilm. Using this extended commercial CFD code and a 128 core compute cluster allowed us to explore the impact of different textile carbon fibre based anode configurations on the electrical performance of the anode in a MFC. The results show that the size of the outer surface of the biofilm determines the quantity of the electrical power delivered by the biofilm. (C) 2019 Elsevier Ltd. All rights reserved.

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