Bitzek, E.: The Origin of Deformation-Induced Topological Anisotropy in Silica Glass. International Conference on the Strength of Materials ICSMA 19, Metz, France (2022)
Meier de Andrade, A.; Bitzek, E.: Fracture in the Presence of Hydrogen - Influence of the Potential. The 11th International Conference on Multiscale Materials Modeling, Prague, Czech Republic (2024)
Meier de Andrade, A.; Bitzek, E.: Fracture in the Presence of Hydrogen - Influence of the Potential. The XXII Brazilian Materials Research Society (B-MRS) Meeting 2024, Santos, Brazil (2024)
Atila, A.: Influence of Structure and Topology on the Deformation Behavior and Fracture of Oxide Glasses. Dissertation, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) (2023)
Poul, M.; Huber, L.; Bitzek, E.; Neugebauer, J.: Systematic Structure Datasets for Machine Learning Potentials: Application to Moment Tensor Potentials of Magnesium and its Defects. arXiv (2022)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…