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
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.