Todorova, M.; Yoo, S.-H.; Surendralal, S.; Neugebauer, J.: Predicting atomic structure and chemical reactions at solid-liquid interfaces by first principles. Operando surface science – Atomistic insights into electrified solid/liquid interfaces (708. WE-Heraeus-Seminar), Physikzentrum, Bad Honnef, Germany (2019)
Neugebauer, J.: Machine Learning in Materials: Screening and Discovery. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan (2019)
Ikeda, Y.; Ishibashi, S.; Neugebauer, J.; Körmann, F.: Tuning stacking-fault energies and local lattice distortions in high-entropy alloys. Theory of Complex Disorder in Materials (TCDM2019) , Linköping, Sweden (2019)
Neugebauer, J.; Surendralal, S.; Todorova, M.: First-principles appraoch to model electrochemical reactions at solid-liquid interfaces. ACS 2019 Fall Meeting & Exhibition, San Diego, CA, USA (2019)
Todorova, M.; Surendralal, S.; Neugebauer, J.: Degradation processes at surfaces and interfaces. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany (2019)
Neugebauer, J.; Huber, L.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio input for multiphysics models: Accuracy, performance and challenges. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Erlangen, Germany (2019)
Neugebauer, J.: Machine Learning in Materials: Screening and Discovery. Gordon Research Conference Physical Metallurgy „Coupling Computation, Data Science and Experiments in Physical Metallurgy“, Manchester, NH, USA (2019)
Alper Kasirga wins the Max Planck Apprenticeship Award and the Max Planck Institute for Sustainable Materials is recognised as an excellent training institution