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MFC research paper focusing on machine learning, neural network, power density

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What they did

System
MFC

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Abstract

Volatile fatty acid (VFA)‐rich leachate generated from acidogenesis of kitchen waste in a leach bed reactor (LBR) was utilized in an earthen microbial fuel cell (EMFC) to generate electricity. Effects of organic loading rate (OLR, 5–10 g VS/L·day) and pH (5–7) on LBR enumerated optimized parameters of OLR (10 g VS/L·day) and pH (5.74) to obtain total VFA (TVFA) of 7.7 ± 0.3 g/L in the leachate, with maximum contribution from acetic acid. Leachate obtained from the LBR was fed to the EMFC with varying OLR (2–7 kg COD/m³·day). The highest power density of 0.76 W/m³ (at OLR 7 kg COD/m³·day) was obtained with higher VFA content in the leachate. A neural network based on the Levenberg–Marquard function effectively predicted chemical oxygen demand and TVFA removal. This study establishes LBR as a techno‐economic method to obtain useful substrate for EMFC. Furthermore, the response modelling of EMFC demonstrates the potential of utilizing machine learning in biological treatment.

Keywords

LeachateAcidogenesisChemical oxygen demandMicrobial fuel cellPulp and paper industryVolatile fatty acids

Identifiers

DOI
10.1111/wej.12861
Journal
Water and Environment Journal
Year
2023