Microbial Fuel Cells (MFCs) are bio-electrochemical devices that directly convert organic substrates into electrical energy, by exploiting micro-organism metabolism at the electrodes. Such a technology has been shown to be promising in dealing with the waste management issue. In fact, by means of these systems, the waste disposal issue may be turned into an economic opportunity. In this work, we develop a three-dimensional numerical model grounded on the lattice Boltzmann method (LBM) to analyze the electrochemical performance of MFCs. Despite a simplified, yet effective, modeling of the electrochemical mechanisms driving the motion of ions inside the reactor, the proposed computational approach is capable of accurately capture the main involved physical phenomena and provide a fair estimation of the ion distribution within the batch reactor. The numerical predictions are then compared with available experimental data for a similar layout of solid-waste MFCs. Despite some differences in the prediction of the concentration-loss phase, which is not clearly observable in the experiments, the results obtained by the proposed methodology show that either power and polarization curves reflect the general trends of MFCs operation. This highlights the significant potential of the present computational approach for the accurate evaluation of MFC performance.

Multiscale methodology for microbial fuel cell performance analysis

Di Ilio G.
;
Falcucci G.
2021-01-01

Abstract

Microbial Fuel Cells (MFCs) are bio-electrochemical devices that directly convert organic substrates into electrical energy, by exploiting micro-organism metabolism at the electrodes. Such a technology has been shown to be promising in dealing with the waste management issue. In fact, by means of these systems, the waste disposal issue may be turned into an economic opportunity. In this work, we develop a three-dimensional numerical model grounded on the lattice Boltzmann method (LBM) to analyze the electrochemical performance of MFCs. Despite a simplified, yet effective, modeling of the electrochemical mechanisms driving the motion of ions inside the reactor, the proposed computational approach is capable of accurately capture the main involved physical phenomena and provide a fair estimation of the ion distribution within the batch reactor. The numerical predictions are then compared with available experimental data for a similar layout of solid-waste MFCs. Despite some differences in the prediction of the concentration-loss phase, which is not clearly observable in the experiments, the results obtained by the proposed methodology show that either power and polarization curves reflect the general trends of MFCs operation. This highlights the significant potential of the present computational approach for the accurate evaluation of MFC performance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/95473
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