Fungal electronics (2021)
Journal Article
Adamatzky, A., Ayres, P., Beasley, A. E., Chiolerio, A., Dehshibi, M. M., Gandia, A., …Wösten, H. A. (2022). Fungal electronics. BioSystems, 212, Article 104588. https://doi.org/10.1016/j.biosystems.2021.104588

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external co... Read More about Fungal electronics.

Fungal architectures (2021)
Exhibition / Performance
Nikolaidou, A., Adamatzky, A., Phillips, N., Roberts, N., & Petrova, I. Fungal architectures. [Installations, Prints]. 13 December 2021 - 19 December 2021. (Unpublished)

"Fungal architectures" arts exhibition presents works inspired by protocognition of fungi and slime moulds and fungal materials. Fungal Architectures is a new cross-disciplinary research project that seeks to develop a fully integrated structural and... Read More about Fungal architectures.

Mem-fractive properties of mushrooms (2021)
Journal Article
Beasley, A. E., Abdelouahab, M. S., Lozi, R., Tsompanas, M. A., Powell, A., & Adamatzky, A. (2022). Mem-fractive properties of mushrooms. Bioinspiration and Biomimetics, 16(6), Article 066026. https://doi.org/10.1088/1748-3190/ac2e0c

Memristors close the loop for I-V characteristics of the traditional, passive, semi-conductor devices. A memristor is a physical realisation of the material implication and thus is a universal logical element. Memristors are getting particular intere... Read More about Mem-fractive properties of mushrooms.

Designing with living materials (2021)
Presentation / Conference
Nikolaidou, A. (2021, September). Designing with living materials. Presented at Climate Action Relay Countdown to COP26|Have cultivated biomaterials come of age?, Online

Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment (2021)
Journal Article
Stillman, N. R., Balaz, I., Tsompanas, M. A., Kovacevic, M., Azimi, S., Lafond, S., …Hauert, S. (2021). Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment. npj Computational Materials, 7(1), Article 150. https://doi.org/10.1038/s41524-021-00614-5

We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. Our work aims to decrease both the time and cost required to develop nanoparticle designs. EVONANO includes a simulator to grow tumours, ex... Read More about Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment.

Protein structured reservoir computing for spike-based pattern recognition (2021)
Journal Article
Tsakalos, K., Ch. Sirakoulis, G., Adamatzky, A., & Smith, J. (2022). Protein structured reservoir computing for spike-based pattern recognition. IEEE Transactions on Parallel and Distributed Systems, 33(2), 322 - 331. https://doi.org/10.1109/TPDS.2021.3068826

Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and cheaper computin... Read More about Protein structured reservoir computing for spike-based pattern recognition.

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.

Living wearables from slime mould and fungi (2021)
Journal Article
Adamatzky, A., Nikolaidou, A., Gandia, A., & Chiolerio, A. (2021). Living wearables from slime mould and fungi. LINKs-series, 93-98

Smart wearables, augmented with soft and liquid electronics, can display sensing, responsive and adaptive capabilities, but they cannot self-grow or self-repair. Living organisms colonising a fabric could be a viable alternative. In the present artic... Read More about Living wearables from slime mould and fungi.

Supplementary material: Evolutionary algorithms designing nano particle cancer treatments with multiple particle types (2021)
Other
Tsompanas, M., Bull, L., Adamatzky, A., & Balaz, I. Supplementary material: Evolutionary algorithms designing nano particle cancer treatments with multiple particle types

Supplementary material: Evolutionary algorithms designing nano particle cancer treatments with multiple particle types

Reactive fungal wearable (2021)
Journal Article
Adamatzky, A., Nikolaidou, A., Gandia, A., Chiolerio, A., & Dehshibi, M. M. (2021). Reactive fungal wearable. BioSystems, 199, Article 104304. https://doi.org/10.1016/j.biosystems.2020.104304

Smart wearables sense and process information from the user’s body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in sof... Read More about Reactive fungal wearable.