Güder, Ü.; Yavaş, A.; Çeken, M.; Yalçın, Ü.; Raabe, D.: A New Type of Steel-Making Crucible from Medieval Anatolia. 7th International Conference of Medieval Archaeology, online, Zagreb, Croatia (2020)
Raabe, D.: Theory-guided design of materials, microstructures and processes. Workshop on the Future of Materials Science, Institute of Nanotechnology, KIT, online, Karlsruhe, Germany (2020)
Raabe, D.; Diehl, M.; Shanthraj, P.; Sedighiani, K.; Roters, F.: Multi-scale and multi-physics simulations of chemo-mechanical crystal plasticity problems for complex engineering materials using DAMASK. Online Colloquium Lecture, Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden (2020)
Kwiatkowski da Silva, A.; Ponge, D.; Gault, B.; Raabe, D.: The Relevance of Interfacial Segregation for Controlling Second Phase Precipitation in Advanced High Strength Steels. TMS 2020 Annual Meeting & Exhibition, San Diego, CA, USA (2020)
Sedighiani, K.; Traka, K.; Diehl, M.; Roters, F.; Bos, K.; Sietsma, J.; Raabe, D.: A Coupled Crystal Plasticity – Cellular Automaton Method for 3D Modeling of Recrystallization: Part I: Crystal Plasticity. International Conference on Plasticity, Damage, and Fracture, Riviera May, Mexico (2020)
Diehl, M.; Kusampudi, N.; Kusche, C.; Raabe, D.; Korte-Kerzel, S.: Combining Experiments, Simulations, and Data Science to Understand Damage in Dual Phase Steels. International Conference on Plasticity, Damage, and Fracture, Riviera May, Mexico (2020)
Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Perlado, J. M.; Marian, J.: Understanding the Plastic Behavior of Tungsten From First Principles to Crystal Plasticity. International Mechanical Engineering Congress & Exposition (IMECE) 2019, Salt Lake City, UT, USA (2019)
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
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.