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Outputs (100)

Microbial fuel cells in the house: A study on real household wastewater samples for treatment and power (2021)
Journal Article

In line with the global movement towards sustainable buildings and dwellings, this work investigated the potential for integrating microbial fuel cell technology into future architecture. Various types of domestic greywater and wastewater from five d... Read More about Microbial fuel cells in the house: A study on real household wastewater samples for treatment and power.

Impact of inoculum type on the microbial community and power performance of urine-fed microbial fuel cells (2020)
Journal Article

Bacteria are the driving force of the microbial fuel cell (MFC) technology, which benefits from their natural ability to degrade organic matter and generate electricity. The development of an efficient anodic biofilm has a significant impact on the p... Read More about Impact of inoculum type on the microbial community and power performance of urine-fed microbial fuel cells.

Effect of microbial fuel cell operation time on the disinfection efficacy of electrochemically synthesised catholyte from urine (2020)
Journal Article

Microbial fuel cells (MFCs) offer an excellent solution to tackle some of the major challenges currently faced by humankind: sustainable energy sources, waste management and water stress. Besides treating wastewater and producing useful electricity f... Read More about Effect of microbial fuel cell operation time on the disinfection efficacy of electrochemically synthesised catholyte from urine.

Evaluation of artificial neural network algorithms for predicting the effect of the urine flow rate on the power performance of microbial fuel cells (2020)
Journal Article

© 2020 The Authors Microbial fuel cell (MFC) power performance strongly depends on the biofilm growth, which in turn is affected by the feed flow rate. In this work, an artificial neural network (ANN) approach has been used to simulate the effect of... Read More about Evaluation of artificial neural network algorithms for predicting the effect of the urine flow rate on the power performance of microbial fuel cells.