Artificial intelligence and machine learning consume energy, and computing in general requires massive amounts of electricity. In order to meet sustainability goals and avoid energy shortages, new strategies for computation are being explored.

In this project we want to explore the possibility of using artificial active matter to develop innovative hardware for non-digital computation and become the active agent in solving computational problems.

We will use our existing library of active materials and explore how they can be driven by different stimuli and interact with their environment to exploit combinations of simple behaviours that can lead to complexity in computation and signaling. Related experiments using active filaments in a nanofabricated network were able to encode different combinatorial problems and the resulting pathways calculated the probability of different solutions. The use of our tiny, ultra-fast active colloids will increase the resilience of the system to environmental changes and allow us to incorporate new, exciting functionalities.

The thesis will include:

• Colloidal synthesis
• Surface modifications
• Material characterization (spectroscopy, electron microscopy, chemical analysis)
• Optical microscopy and microfluidic techniques to observe microscale motion
• Microfluidics
• Data collection and data treatment
• Writing scientific papers and reports and present results (in form of posters and conference talks)

Further information

• Sharan P, Maslen C, Altunkeyik B, Rehor I, Simmchen J, Montenegro Johnson,T. Advanced Intelligent Systems 2021, 3 (11), 2100068
• Wittmann M, VoigtmannM, Simmchen, J. Small 2023, 19 (15), 2206885
• Niese, L.; Wang, L.; Das, S.; Simmchen, J. Soft Matter 2020, 16, 10585–10590.
• Nicolau Jr, D. V.; Lard, M.; Korten, T., et al. Proceedings of the National Academy of Sciences 2016, 113, 2591–2596