Sato, H.; Zaefferer, S.: A study on the formation mechanisms of butterfly-type martensite in Fe–30% Ni alloy using EBSD-based orientation microscopy. Acta Materialia 57 (6), pp. 1931 - 1937 (2009)
Sato, H.; Zaefferer, S.; Watanabe, Y.: In-situ Observation of Butterfly-type Martensite in Fe-30mass%Ni Alloy during Tensile Test Using High-resolution EBSD. ISIJ International 49, pp. 1784 - 1791 (2009)
Zaefferer, S.; Sato, H.: Investigation of the formation mechanism of martensite plates in Fe-30%Ni by a high resolution orientation microscopy in SEM. ESOMAT 2006, Bochum (2006)
Sato, H.; Zaefferer, S.: A study on the crystal orientation relationship of butterfly martensite in an Fe30 % Ni alloy by 3-D EBSD-based orientation microscopy. Microscopy Conference 2005, Davos, Switzerland (2005)
Sato, H.; Zaefferer, S.: 3D-analysis of the crystal orientation relationship and growth process of lenticular martensite in Fe–30mass%Ni alloy. DPG Frühjahrstagung, Berlin, Germany (2005)
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
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
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.