Diehl, M.; Kusampudi, N.; Kusche, C.; Raabe, D.; Korte-Kerzel, S.: Combining Experiments, Simulations, and Data Science to Understand Damage in Dual Phase Steels. International Conference on Plasticity, Damage, and Fracture, Riviera May, Mexico (2020)
Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Potential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Po-tential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Chang, Y.: Challenges and opportunities associated to the characterization of H/D in Ti and its alloys with atom probe tomography. Dissertation, RWTH Aachen University (2019)
Choi, W. S.: Deformation mechanisms and the role of interfaces in face-centered cubic Fe-Mn-C micro-pillars. Dissertation, RWTH Aachen, Aachen, Germany (2018)
Morsdorf, L.: Fundamentals of ferrous low-carbon lath martensite: from the as-quenched, to tempered and deformed states. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Wu, L.: Characterization of the microstructure and impurities of Al–Mg–Sc alloy produced by Laser Additive Manufacturing. Master, RWTH Aachen, Aachen, Germany (2016)
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.