On August 1st Menachem (Nachi) Stern will start as tenure track group leader at AMOLF. He will lead the Learning Machines group, which will be shared between the autonomous matter and information in matter research themes at AMOLF. Stern’s research efforts will focus on the physics of learning in natural and synthetic systems. Such learning machines can adopt desirable properties and functions given real world examples and environments. Leveraging the advances of statistical learning theory in physical machines, physical learning is a promising bridge between computational machine learning and biology, and enables the development of new classes of bio-inspired smart metamaterials that adapt in-situ to users’ needs.
A theoretical physicist by training, Stern did his Ph.D. at The University of Chicago, in the group of Prof. Arvind Murugan. There he investigated mechanical systems like spring networks and self-folding origami as models for novel computation and learning. He is currently a postdoctoral fellow at The University of Pennsylvania, studying various aspects of physical learning algorithms and their implementations as learning machines.
Four PhD students defended their thesis and are about to take the next steps in their career. Congratulations to Colin Meulblok (Mechanical Metamaterials), Francesca Scalerandi (Hybrid Nanosystems), Vashist Gangigude Ramesh (Interacting Photons), and Parisa Omidvar (Hypersmart Matter). We wish you all the best in your next steps!
AMOLF group leaders Professor Wiebke Albrecht and Professor Bruno Ehrler have received an NWO ENW-M2 grant for their joint research project, The Dynamic Atomic Interface between Halide Perovskites and Metals. The insights gained will pave the way for sustainable, high-performance solar energy and information technology. Wiebke and Bruno will each hire a PhD student for this project. The grant amounts to €800.000.
On October 8, Professor Wim Noorduin and his collaborator Professor Arian van Asten (University of Amsterdam) presented their scientific journey in a video to the audience at the ‘Avond van Wetenschap en Maatschappij’. They did so alongside the other nominees for the Huibregtsen Prize.
Silicon solar panels are rigid and heavy, and many rooftops cannot support them. This creates a need for thin, flexible solar cells that can be integrated into building materials. However, making silicon solar cells thinner makes it harder to trap light inside the material. Researchers in the 3D Photovoltaics group found a fascinating way to overcome this challenge using a phenomenon called hyperuniform disorder. They publish their findings in the journal ACS Photonics.
The researchers were able to make highly efficient silicon solar cell materials that are 30 times thinner than conventional ones. They managed to do this by integrating a layer of nanometer sized structures on top of the material. Up close, this pattern looks random, but it is remarkably when you step back: no clumps, no gaps, and no repeating pattern. This is called hyperuniform disorder (or HUD).
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