Eventos Anais de eventos
ENCIT 2022
19th Brazilian Congress of Thermal Sciences and Engineering
Performance prediction of microbial fuel cells for acid mine drainage treatment and energy production using least squares fitting method
Submission Author:
William Francisconi Taufemback , SC
Co-Authors:
William Francisconi Taufemback, Tatiana Pineda, Priscila Cardoso Calegari, Derce de Oliveira Souza Recouvreux, REGINA ANTONIO, Elise Watzko
Presenter: William Francisconi Taufemback
doi://10.26678/ABCM.ENCIT2022.CIT22-0210
Abstract
One of the impacts of coal mining is the contamination by Acid Mine Drainage (AMD). Among the alternatives proposed for the AMD treatment, a promising one is through Microbial Fuel Cells (MFCs), whose electrical performance can be characterized by obtaining polarization curves (PCs). Thus, this study proposes an experimental validation of a steady state a model for the prediction of the characteristic equation of the PC of MFCs, applying a least squares fitting to estimate the parameters. The experiments consisted of two double-chamber MFCs operating in fed-batch for 75 days, each separated by different proton exchange membranes (PEM): one used Nafion™ 117 (MFC-NA) and another, bacterial cellulose (MFC-BC). The cathodic chambers were filled with AMD and inoculated with sulfate-reducing bacteria. Experimental PC obtained for MFC-BC showed higher power and current densities than that for MFC-NA. The comparison of the curves obtained by the fitting with experimental data from a study found in the literature, as well as the data from experiments in this paper, demonstrate the potential of the method proposed. In future works, it is expected to test the fitting methodology developed in this paper for different MFC systems, aiming to improve its predictive ability.
Keywords
Microbial fuel cell, Least squares fitting, acid mine drainage, Polarization curve, mathematical modeling
