Zaafarani, N.; Singh, R.; Zaefferer, S.; Roters, F.; Raabe, D.: 3D experimental investigation and crystal plasticity FEM simulation of the texture and microstructure below a nanoindent in a Cu-single crystal. 6th European Symposium on nano-mechanical Testing (Nanomech 6), Hückelhoven, Germany (2005)
Konrad, J.; Raabe, D.; Zaefferer, S.: Deformation Behavior of a Fe3Al Alloy During Thermomechanical Treatment. MRS Fall Meeting, Boston, MA, USA (2004)
Thomas, I.; Zaefferer, S.; Friedel, F.; Raabe, D.: Orientation dependent growth behaviour of subgrain structures in IF steel. 2nd International Joint Conference on Recrystallization and Grain Growth, Annecy, France (2004)
Konrad, J.; Raabe, D.; Zaefferer, S.: Nucleation Mechanisms of Recrystallization in Warm Rolled Fe3Al Base Alloys. Discussion Meeting on the Development of Innovative Iron Aluminium Alloys, MPIE, Düsseldorf, Germany (2004)
Wöllmer, S.; Zaefferer, S.; Göken, M.; Mack, T.; Glatzel, U.: Characterization of phases of aluminized nickel base superalloys. Intern. Conf. on Strength of Materials (ICSMA 13), Budapest, Hungary (2003)
Zaefferer, S.; Motaman, S. A. H.: Metallic Materials (Microstructure, Microscopy, Modelling). Lecture: SS 2021, RWTH Aachen University, April 12, 2021 - July 23, 2021
Zaefferer, S.: Fundamentals and practical aspects of texture and microstructure measurements using EBSD-based orientation microscopy and related techniques. Lecture: January 2020, IIT Madras, India, 2020-01
Zaefferer, S.: Fundamentals and practical aspects of texture and microstructure measurements using EBSD-based orientation microscopy and related techniques. Lecture: Febuary and March 2020, MPIE Düsseldorf, 2020-01
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…