Hickel, T.; Zendegani, A.; Körmann, F.; Neugebauer, J.: Energetics of non-stoichiometric stacking faults in Fe–Nb alloys: An ab initio study. TMS 2019 Annual Meeting, San Antonio, TX, USA (2019)
Neugebauer, J.; Surendralal, S.; Todorova, M.: Extending First-Principles Calculations to Model Electrochemical Reactions at the Solid-Liquid Interface. Towards Reality in Nanoscale Materials X, Levi, Finnland (2019)
Neugebauer, J.; Janßen, J.; Körmann, F.; Hickel, T.; Grabowski, B.: Exploration of large ab initio data spaces to design materials with superior mechanical properties. Physics and Theoretical Division Colloquium, Los Alamos, NM, USA (2019)
Todorova, M.; Yoo, S.-H.; Surendralal, S.; Neugebauer, J.: Modelling electrochemical solid/liquid interfaces by first principles calculations. 19th International Workshop on Computational Physics and Material Science: Total Energy and Force Methods, ICTP, Trieste, Italy (2019)
Ikeda, Y.; Körmann, F.; Neugebauer, J.: Impact of chemical compositions and interstitial alloying on the stacking fault energy of CrMnFeCoNi-based HEAs from first principles. The 2nd International Conference on High-Entropy Materials , Jeju, South Korea (2018)
Neugebauer, J.: Exploration of large ab initio data spaces to design structural materials with superior mechanical properties. Multiscale Materials Modeling (MMM 2018) Conference, Osaka, Japan (2018)
Neugebauer, J.: Fundamental compositional limitations in the thin film growth of metastable alloys. 3rd Conference on Advanced Functional Materials (AFM2018), Vildmarkshotellet Kolmården, Norrköping, Sweden (2018)
Neugebauer, J.: Modelling thermodynamics and kinetics of general grain boundaries: Challenges and successes. Thermec 2018 Conference, Paris, France (2018)
Neugebauer, J.: First-principles approaches for charged defects in low dimensional systems. Conference on Physics of Defects in Solids, Trieste, Italy (2018)
Neugebauer, J.: Understanding fundamental doping and stoichiometry limits in semiconductors by ab initio modelling. EDS 2018 Conference, Thessaloniki, Greece (2018)
Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Efficient approach to compute melting properties fully from ab initio with application to Cu. CALPHAD XLVII Conference, Querétaro, México (2018)
Neugebauer, J.: Machine learning as tool to enhance ab initio based alloy design. Workshop: “Machine learning and data analytics in advanced metals processing", Manchester, UK (2018)
Scientists at the Max Planck Institute for Sustainable Materials have developed a carbon-free, energy-saving method to extract nickel for batteries, magnets and stainless steel.
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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