Eisenlohr, P.; Güvenc, O.; Amberger, D.: Influence of hard-phase skeleton on creep strength of Mg-alloys - Insights from full field deformation simulations. 9th Int. Conf. Magnesium Alloys and their Applications, Vancouver, Canada (2012)
Kords, C.; Eisenlohr, P.; Roters, F.: A nonlocal crystal plasticity model used to solve heterogeneous boundary value problems for 3D microstructures. 18th International Symposium on Plasticity & Its Current Applications, San Juan, Puerto Rico (2012)
Liu, B.; Raabe, D.; Eisenlohr, P.; Roters, F.: Dislocation-hexagonal dislocation network interaction in BCC metals. 18th International Symposium on Plasticity & Its Current Applications, San Juan, Puerto Rico (2012)
Roters, F.; Eisenlohr, P.; Tjahjanto, D. D.; Kords, C.; Diehl, M.; Raabe, D.: DAMASK: The Düsseldorf Advanced Material Simulation Kit for studying crystal plasticity using FEM and FFT based numerical solvers. 18th International Symposium on Plasticity & Its Current Applications, San Juan, Puerto Rico (2012)
Kords, C.; Jäpel, T.; Eisenlohr, P.; Roters, F.: Residual stress prediction by considering dislocation density advection in 3D applied to single-crystal bending. Euromat 2011, Montpellier, France (2011)
Kords, C.; Jäpel, T.; Eisenlohr, P.; Roters, F.: Residual stress prediction by considering dislocation density advection in 3D applied to single-crystal bending. 2nd International Conference on Material Modelling ICMM 2, Paris, France (2011)
Roters, F.; Diehl, M.; Eisenlohr, P.; Lebensohn, R. A.: Solving finite-deformation crystal elasto-viscoplasticity with a fast Fourier transformation-based spectral method. 2nd International Conference on Material Modelling ICMM 2, Paris, France (2011)
Steinmetz, D.; Roters, F.; Eisenlohr, P.; Raabe, D.: A dislocation density-based constitutive model for TWIP steels. 1st International Conference on High Manganese Steels, Seoul, South Korea (2011)
Roters, F.; Eisenlohr, P.; Raabe, D.: Eine modulare Kristallplastizitäts Implementierung für Anwendungen vom Einkristall bis zum Bauteil. 14. Workshop Simulation in der Umformtechnik, Dortmund, Germany (2011)
Eisenlohr, P.; Roters, F.; Kords, C.; Diehl, M.; Lebensohn, R.A.; Raabe, D.: Combining characterization and simulation of grain-scale plasticity in three dimensions. EBSD Conference 2011 of the Royal Microscopical Society, Düsseldorf, Germany (2011)
Roters, F.; Eisenlohr, P.; Tjahjanto, D. D.; Kords, C.; Raabe, D.: A modular crystal plasticity framework applicable from component to single grain scale. IUTAM Symposium Linking Scales in Computations: From Microstructure to Macro-scale Properties, Pensacola, FL, USA (2011)
Eisenlohr, P.; Kords, C.; Roters, F.; Raabe, D.: How to capture mesoscale plastic strain gradient effects in a physical way -- a look at dislocation mechanics and computational aspects. MST Symposium, Los Alamos National Laboratory, Los Alamos, NM, USA (2011)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
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.