Roters, F.; do Nascimento, A. W. P.; Roongta, S.; Diehl, M.: An optimized method for the simulation-based determination of initial parameters of advanced yield surfaces for sheet metal forming applications. Complas 2021, online (2021)
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)
Roters, F.; Diehl, M.; Sedighiani, K.: (Re-) formulation of dislocation density based crystal plasticity models in view of insights from parameter determination. Oberwolfach Workshop: Mechanics of Materials: Towards Predictive Methods for Kinetics in Plasticity, Fracture, and Damage, Oberwolfach, Germany (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)
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)
Sedighiani, K.; Traka, K.; Diehl, M.; Roters, F.; Sietsma, J.; Raabe, D.: Determination and validation of BCC crystal plasticity parameters for a wide range of temperatures and strain rates. 7th Conference on Recrystallization and Grain Growth, REX 2019, Ghent, Belgium (2019)
Shah, V.; Diehl, M.; Roters, F.: Prediction of Nucleation Sites for Recrystallization using Crystal Plasticity Simulations. 7th International Conference on Recrystallization and Grain Growth, Ghent, Belgium (2019)
Diehl, M.; Roters, F.; Raabe, D.: Coupled Experimental-Computational Investigations of Grain Scale Mechanics in Complex Metallic Microstructures. 15th U.S. National Congress on Computational Mechanics, Ausrin, TX, USA (2019)
Han, F.; Diehl, M.; Roters, F.; Raabe, D.: Multi-scale modeling of plasticity. ICIAM 2019 - The 9th International Congress on Industrial and Applied Mathematics, Valencia, Spain (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
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.
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.