Microbial Fuel Cell Research Paper

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The RBF neural network and ELM neural network were used to perform nonlinear system regression in the later stage of SMFC start-up and using the regression network to forecast part of the data.

The experimental results show that the ELM neural network is more excellent in forecasting SMFC system.

Therefore, it is necessary to find a suitable neural network to fit the nonlinear model between various parameters in the start-up phase.

As far as we know, there is no study on the relationship between p H, power generation and temperature during the start-up of microbial fuel cells.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Sediment microbial fuel cells (SMFCs) are a typical microbial fuel cell without membranes.They are a device developed on the basis of electrochemistry and use microbes as catalysts to convert chemical energy stored in organic matter into electrical energy.This study selected a single-chamber SMFC as a research object, using online monitoring technology to accurately measure the temperature, p H, and voltage of the microbial fuel cell during the start-up process.For the SMFC system, due to its more complex environmental conditions, stronger coupling, and nonlinear characteristics than MFC [21], sometimes it is inconvenient for online detection of certain parameters.Computational methods play a critical role in developing fuel cells with optimum performance in a wide range of operating conditions. [22] developed algorithms for the simulation of reactive flows through micro- and nanoscale porous media via the Lattice Boltzmann method are presented and for the first time used in the field of microbial fuel cells. used EKF algorithm to estimate battery parameters in real time [23, 24]. [25] used Gause-Newton algorithm to solve the parameters iteratively. studied particle filter-based parameter estimation method [26]. Identified the battery parameters through recursive least square method [27, 28].This article will provide important guidance for shortening start-up time and increasing power output.Microbial fuel cell (MFC) is being viewed as a potential bio-electrochemical device capable of producing energy in the form bioelectricity apart from wastewater treatment [1–3] which has been widely investigated in recent years. [4] described enzymatic biofuel cell based on enzyme modified anode and cathode electrodes are both powered by ethanol and operate at ambient temperature. [5] reviewed recent articles about the application of MFCs to solid substrates treatment and valorisation and the contribution that BESs and MFC could give to the development of a more sustainable waste management. [6] investigated the influence of microelectrogenesis on PAHs degradation and detoxification operated by Pseudomonadaceae, Bacillaceae, Staphylococcaceae, and Enterobacteriaceae in water environment.The single-chamber SMFC consisted of an anode and cathode placed in a Plexiglas cylindrical chamber (purchased from Ji’nan lanyo Technology Ltd.) with a length of 49 cm and a diameter of 9 cm (empty bed volume of 2000 m L).The anode and cathode electrodes were made of plain carbon felts (purchased from Beijing Jinglong Special Carbon Technology Co.Compared with MFC, Sediment microbial fuel cells (SMFCs) are a special application of MFCs for sustainable electricity production [7] and are also the most common membrane free microbial fuel cells which are considered as alternative renewable energy sources for remote environmental monitoring via an energy conversion system.SMFC generates electrical energy through the oxidation of organic matter in the presence of fermentative bacteria under mild operating conditions [8].

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