Freysoldt, C.: Exploring data-rich materials analytics with machine learning: how and why. Physikalisches Kolloquium, Universität Marburg, Marburg, Germany (2023)
Freysoldt, C.; Hickel, T.; Janßen, J.; Wang, N.; Zendegani, A.: High-throughput optimization of finite temperature phase stabilities: Concepts and application. Coffee with Max Planck, virtual seminar organized by the MPIE, Düsseldorf, Germany (2021)
Hickel, T.; Freysoldt, C.; Janßen, J.; Wang, N.; Zendegani, A.: High-throughput optimization of finite temperature phase stabilities: Concepts and application. Coffee with Max Planck, virtual seminar organized by the MPIE, Düsseldorf, Germany (2021)
Freysoldt, C.: Modelling of charged point defects with density-functional theory. 4th International Workshop on Models and Data for Plasma-Material Interaction in Fusion Devices, National Institute for Fusion Science (NIFS), Toki, Japan (2019)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.