Bioelectricity generation in an integrated system combining microbial fuel cell and tubular membrane reactor: effects of operation parameters performing a microbial fuel cell-based biosensor for tubular membrane bioreactor

A bio-cathode microbial fuel cell (MFC) with tubular membrane was integrated to construct a microbial fuel cell-tubular membrane bioreactor (MFC-TMBR) system, in which the bio-cathode MFC was developed as a biosensor for COD real-time monitoring in TMBR and the performance was analyzed in terms of its current variation caused by operation parameters. With a constant anode potential, the effect of HRT demonstrated that higher rate of mass transport increased the response of the system. The system was further explored an inverse relationship between TMP and current peak by using EPS concentration under the different MLSS concentration. The sensor output had a linear relationship with COD up to 1000mg/L (regression coefficient, R(2)=0.97) and MLSS (regression coefficient, R(2)=0.94). The simple and compact bio-cathode MFC biosensor for TMBR using MFC-TMBR integrated system showed promising potential for direct and economical COD online monitoring, and provided an opportunity to widen the application of MFC-based biosensor.

Neural network processing of microbial fuel cell signals for the identification of chemicals present in water

Biosensing is emerging as an important element of water quality monitoring. This research demonstrated that microbial fuel cell (MFC)-based biosensing can be integrated with artificial neural networks (ANNs) to identify specific chemicals present in water samples. The non-fermentable substrates, acetate and butyrate, induced peak areas (PA) and peak heights (PH) that were generally larger than those caused by the injection of fermentable substrates, glucose and corn starch. The ANN successfully identified peaks associated with these four chemicals under a variety of experimental conditions and for two MFCs that had different levels of sensitivity. ANNs that employ the hyperbolic tangent sigmoid transfer function performed better than those using non-continuous transfer functions. ANNs should be integrated into water quality monitoring efforts for smart biosensing.