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Experiments · Simulations · Metamaterials · Fun
Our research team develops new materials capable of altering their physical properties and mechanical behavior on demand. We harness the mighty power of machine learning to uncover structure–property relationships and design materials for various exciting applications such as soft robotics.
Latest News
Successful Defence of Dan Wang
Ms. Dan Wang received the highest grade (1.0) for her thesis "Mechanical Metamaterials with Explicitly and Implicitly Defined Geometry". It was a rewarding year-long journey exploring nonconventional ways to define unit-cell geometry and link it to mechanical properties. Dan did a superb job employing the level-set method, FEniCS for homogenization, and generative machine learning to design metamaterials with desired properties. We wish her great success in her future career!
Farewell, Michael
After two productive years here in Freiburg, Michael is returning to CTU Prague to continue his journey as a Dozent. Michael brought many new ideas to our group, and we’re sad to see him go. But we’ll definitely continue to collaborate — and hopefully have a chance to play some disc golf together in the future :) All the best!
Soft Robotic Engines with Non-Reciprocal Motion by Physical Intelligence
The third collaborative paper in the series devoted to the unusual behavior of hydrogel-based metamaterials has been published in Advanced Materials. In "Soft Robotic Engines with Non-Reciprocal Motion by Physical Intelligence", my contribution was relatively small, but the paper itself is absolutely fascinating. It demonstrates how non-reciprocal motion can be achieved through the smart design of hydrogels. The research group of Prof. Andreas Walther are absolute magicians when it comes to chemistry!