Ikeda, Y.; Ishibashi, S.; Neugebauer, J.; Körmann, F.: Tuning stacking-fault energies and local lattice distortions in high-entropy alloys. Theory of Complex Disorder in Materials (TCDM2019) , Linköping, Sweden (2019)
Neugebauer, J.; Huber, L.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio input for multiphysics models: Accuracy, performance and challenges. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Erlangen, Germany (2019)
Ikeda, Y.; Körmann, F.; Neugebauer, J.: Impact of Interstitial Alloying of High Entropy Alloys from First Principles. TMS 2019, San Antonio, TX, USA (2019)
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.