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.

Modelling microbial fuel cells using Lattice Boltzmann methods (2018)
Journal Article
Tsompanas, M. A., Adamatzky, A., Ieropoulos, I., Phillips, N., Sirakoulis, G., & Greenman, J. (2019). Modelling microbial fuel cells using Lattice Boltzmann methods. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6(16), 2035-2045. https://doi.org/10.1109/TCBB.2018.2831223

An accurate modelling of bio-electrochemical processes that govern Microbial Fuel Cells (MFCs) and mapping their behaviour according to several parameters will enhance the development of MFC technology and enable their successful implementation in we... Read More about Modelling microbial fuel cells using Lattice Boltzmann methods.

Towards implementation of cellular automata in Microbial Fuel Cells (2017)
Journal Article
Sirakoulis, G. C., Tsompanas, M. A., Adamatzky, A., Greenman, J., & Ieropoulos, I. (2017). Towards implementation of cellular automata in Microbial Fuel Cells. PLoS ONE, 12(5), e0177528. https://doi.org/10.1371/journal.pone.0177528

© 2017 Tsompanas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are... Read More about Towards implementation of cellular automata in Microbial Fuel Cells.

Cellular non-linear network model of microbial fuel cell (2017)
Journal Article
Sirakoulis, G. C., Phillips, N., Tsompanas, M. A., Adamatzky, A., Ieropoulos, I., & Greenman, J. (2017). Cellular non-linear network model of microbial fuel cell. BioSystems, 156-157, 53-62. https://doi.org/10.1016/j.biosystems.2017.04.003

© 2017 Elsevier B.V. A cellular non-linear network (CNN) is a uniform regular array of locally connected continuous-state machines, or nodes, which update their states simultaneously in discrete time. A microbial fuel cell (MFC) is an electro-chemica... Read More about Cellular non-linear network model of microbial fuel cell.

On hybrid circuits exploiting thermistive properties of slime mould (2016)
Journal Article
Walter, X. A., Horsfield, I., Mayne, R., Ieropoulos, I. A., & Adamatzky, A. (2016). On hybrid circuits exploiting thermistive properties of slime mould. Scientific Reports, 6(23924), https://doi.org/10.1038/srep23924

Slime mould Physarum polycephalum is a single cell visible by the unaided eye. Let the slime mould span two electrodes with a single protoplasmic tube: if the tube is heated to approximately ≈40 °C, the electrical resistance of the protoplasmic tube... Read More about On hybrid circuits exploiting thermistive properties of slime mould.