Zaafarani, N.; Raabe, D.; Singh, R. N.; Roters, F.; Zaefferer, S.; Zambaldi, C.: 3D EBSD characterization and crystal plasticity FE simulation of the texture and microstructure below a nanoindent in Cu. Plasticity Conference 2006, Halifax, Canada (2006)
Raabe, D.: Recent Advances in Crystal Mechanics and Chitin Composites. Physics Colloquium at the Physics Department of the Technical University Dresden, Dresden, Germany (2006)
Godara, A.; Raabe, D.: Strain localization and microstructure evolution during plastic deformation of fiber reinforced polymer composites investigated by digital image correlation. Department Seminar, MPIE, Düsseldorf (Germany) (2006)
Bastos, A.; Zaefferer, S.; Raabe, D.: Orientation microscopy on electrodeposited samples. 13th Conference and Workshop on Electron Backscatter Diffraction, Oxford, UK (2006)
Raabe, D.: Advances in Constitutive Modeling in Crystal Plasticity FEM. Colloquium Lecture at the Department for Aeronautics at the Massachusetts Institute of Technology, Cambridge, USA (2006)
Godara, A.; Raabe, D.: Micromechanical behavior of thermoplastic matrix composites by digital image correlation. SAMPE Europe - Society for the Advancement of Material and Process Engineering (SAMPE 2006), Paris (2006)
Roters, F.; Ma, A.; Zaafarani, N.; Raabe, D.: Crystal plasticity FEM modeling at large scales and at small scales. GAMM annual meeting, Berlin, Germany (2006)
Zaafarani, N.; Raabe, D.; Singh, R. N.; Roters, F.: Three dimensional investigation of the texture and microstructure below a nanoindent in a Cu single crystal using 3D EBSD and crystal plasticity finite element simulations. DPG Frühjahrstagung, Dresden, Germany (2006)
Bastos, A.; Zaefferer, S.; Raabe, D.: Characterization of microstructure and Texture of nanostructure electrodeposited NiCo samples by use of Electron Backscatter Diffraction (EBSD). DPG – Spring meeting, Dresden, Germany (2006)
Romano, P.; Barani, A.; Ponge, D.; Raabe, D.: Design of High-Strength Steels by microalloying and thermomechanical treatment. TMS 2006, San Antonio, TX, USA (2006)
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
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…
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…