Song, J.; Kostka, A.; Veehmayer, M.; Raabe, D.: Hierarchical microstructure of explosive joints: Example of titanium to steel cladding. Materials Science and Engineering A 528, pp. 2641 - 2647 (2011)
Kostka, A.; Song, J.; Raabe, D.; Veehmayer, M.: Structural characterization and analysis of interface formed by explosion cladding of titanium to low carbon steel. 19th International Symposium on Metastable, Amorphous and Nanostructured Materials (ISMANAM), Moscow, Russia (2012)
Kostka, A.; Song, J.; Raabe, D.; Veehmayer, M.: Microstructure and properties of interfaces formed by explosion cladding of Ti-Steel. XXI Conference on Applied Crystallography, Zakopane, Poland (2009)
Kostka, A.; Song, J.; Raabe, D.; Veehmayer, M.: Microstructure and properties of interfaces formed by explosion cladding of Ti-Steel. XXI Conference on Applied Crystallography, Zakopane, Poland (2009)
Song, J.: Explosive Cladding of Titanium onto Low Carbon Steel. International SurMat Workshop, Department of Material Science and Engineering, Ruhr-Universität Bochum, Bochum, Germany (2008)
Song, J.: Microstructure and properties of interfaces formed by explosion cladding of Titanium to low Carbon steel. Dissertation, Ruhr-University Bochum, Bochum, Germany (2011)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
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…