Gomell, L.: Advancing the understanding of the microstructure-property relationship in non-toxic and cost-effective thermoelectric Heusler compounds. Dissertation, Fakultät für Georessourcen und Materialtechnik der RWTH Aachen, Germany (2022)
Yilmaz, C.: Influence of Processing Parameters, Crystallography and Chemistry of Defects on the Microstructure and Texture Evolution in Grain-Oriented Electrical Steels. Dissertation, RWTH Aachen, Germany (2022)
Prithiv, T. S.: Grain boundary segregation of boron and carbon and their local chemical effects on the phase transformations in steels. Dissertation, Faculty of Georesources and Materials Engineering of the RWTH Aachen, Germany (2021)
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
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.