Saksena, A.; Kubacka, D.; Gault, B.; Spieker, E.; Kontis, P.: The effect of γ matrix channel width on the compositional evolution in a multi-component nickel-based superalloy. Scripta Materialia 219, 114853 (2022)
Lilensten, L.; Kostka, A.; Lartique-Korinek, S.; Gault, B.; Tin, S.; Antonov, S.; Kontis, P.: Partitioning of Solutes at Crystal Defects in Borides After Creep and Annealing in a Polycrystalline Superalloy. JOM-Journal of the Minerals Metals & Materials Society 73, pp. 2293 - 2302 (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.