Roters, F.: Numerische Simulation der Metallumformung und Rekristallisation. Workshop, Simulation und numerische Modellierung, Materials Valley e.V., Mainz (2003)
Wang, Y.; Roters, F.; Raabe, D.: Simulation of Texture and Anisotropy during Metal Forming with Respect to Scaling Aspects. 1st Colloquium Process Scaling, Bremen, Germany (2003)
Roters, F.: Crystal plasticity FEM from grain scale plasticity to anisotropic sheet forming behaviour. 13th international Workshop on Computational Modelling of the Mechanical Behaviour of Materials, Magdeburg, Germany (2003)
Raabe, D.; Helming, K.; Roters, F.; Zhao, Z.; Hirsch, J.: A Texture Component Crystal Plasticity Finite Element Method for Scalable Large Strain Anisotropy Simulations. ICOTOM 13, Seoul, South Korea (2002)
Sedighiani, K.; Diehl, M.; Traka, K.; Roters, F.; Sietsma, J.; Raabe, D.: On the determination of constitutive parameters for a physics-based crystal plasticity model from macro-scale behavior. Meeting Materials 2018 , M2i Conference, Noordwijkerhout, The Netherlands (2018)
Shah, V.; Diehl, M.; Roters, F.: Prediction of Nucleation Sites During Recrystallization. M2i conference “Meeting Materials”, Noordwijkerhout, The Netherlands (2018)
Reuber, J. C.; Eisenlohr, P.; Roters, F.: Boundary Layer Formation in Continuum Dislocation Dynamics. Dislocations 2016, Purdue University, West Lafayette, IN, USA (2016)
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
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.