Wang, Z.; Gu, J.; An, D.; Liu, Y.; Song, M.: Characterization of the microstructure and deformation substructure evolution in a hierarchal high-entropy alloy by correlative EBSD and ECCI. Intermetallics 121, 106788 (2020)
An, X.; Wang, Z.; Ni, S.; Song, M.: The tension-compression asymmetry of martensite phase transformation in a metastable Fe40Co20Cr20Mn10Ni10 high-entropy alloy. Science China Materials 63 (9), pp. 1797 - 1807 (2020)
Wang, Z.; Lu, W.; Raabe, D.; Li, Z.: On the mechanism of extraordinary strain hardening in an interstitial high-entropy alloy under cryogenic conditions. Journal of Alloys and Compounds 781, pp. 734 - 743 (2019)
Li, Z.; Su, J.; Lu, W.; Wang, Z.; Raabe, D.: Metastable high-entropy alloys: design, structure and properties. 2nd International Conference on High-Entropy Materials (ICHEM 2018), Jeju, South Korea (2018)
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.