Zambaldi, C.; Zaefferer, S.; Wright, S. I.: Determination of texture and microstructure of ordering domains in gamma-TiAl. Electron Backscatter Diffraction Meeting by the Royal Microscopical Society, University of Sheffield, Sheffield, UK (2008)
Zaefferer, S.; Romano, P.: Attempt to identify and quantify microstructural constituents in low-alloyed TRIP steels by simultaneous EBSD and EDS measurements. M&M 2007, Microscopy and Microanalysis 2007 Meeting, Ft. Lauderdale, FL, USA (2007)
Frommert, M.; Dorner, D.; Lahn, L.; Raabe, D.; Zaefferer, S.: 3D Investigation of Early Stages of Recrystallization in Deformed Goss-Oriented Fe3%Si Single Crystals. The Third International Conference on Recrystallization and Grain Growth ReX & GG III, Jeju Island, South Korea (2007)
Zaefferer, S.: Some ideas on the formation mechanisms and intensity of electron backscatter diffraction patterns. 14th Conference on Electron Backscatter Diffraction, New Lanark, Scotland, UK (2007)
Bastos, A.; Zaefferer, S.; Raabe, D.: 3 Dimensional EBSD study of the relationship between triple junctions and columnar grain in electrodeposited materials. Electron Back Scatter Diffraction Meeting 2007, New Lanark, Scotland, UK (2007)
Bastos da Silva, A. F.; Zaefferer, S.; Raabe, D.: Three Dimension Characterization of Electrodeposited Samples. MRS Fall Meeting, Boston, MA, USA (2005)
Dorner, D.; Zaefferer, S.: 3D reconstruction of an abnormally growing Goss grain in Fe3%Si by FIB serial sectioning and EBSD. DPG-Jahrestagung 2005, Berlin, Germany (2005)
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)
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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…