All Outputs (2)

Neural networks predicting microbial fuel cells output for soft robotics applications (2021)
Journal Article
Tsompanas, M. A., You, J., Philamore, H., Rossiter, J., & Ieropoulos, I. (2021). Neural networks predicting microbial fuel cells output for soft robotics applications. Frontiers in Robotics and AI, 8, Article 633414. https://doi.org/10.3389/frobt.2021.633414

The development of biodegradable soft robotics requires an appropriate eco-friendly source of energy. The use of Microbial Fuel Cells (MFCs) is suggested as they can be designed completely from soft materials with little or no negative effects to the... Read More about Neural networks predicting microbial fuel cells output for soft robotics applications.

Artificial neural network simulating microbial fuel cells with different membrane materials and electrode configurations (2019)
Journal Article
Tsompanas, M. A., You, J., Wallis, L., Greenman, J., & Ieropoulos, I. (2019). Artificial neural network simulating microbial fuel cells with different membrane materials and electrode configurations. Journal of Power Sources, 436, Article 226832. https://doi.org/10.1016/j.jpowsour.2019.226832

© 2019 Elsevier B.V. Microbial fuel cells (MFCs) are gaining interest due to higher power production achieved by deep analysis of their characteristics and their effect on the overall efficiency. To date, investigations on MFC efficiency, can only be... Read More about Artificial neural network simulating microbial fuel cells with different membrane materials and electrode configurations.