Gong, Y.; Ikeda, Y.; Körmann, F.; Neugebauer, J.: Ab initio computation of phase stability and interstitial alloying in bcc compositionally complex alloys. International Conference on High-Entropy Materials (ICHEM 2023), Knoxville, TN, USA (2023)
Zhu, L.-F.; Neugebauer, J.; Grabowski, B.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential. CALPHAD L Conference, Cambridge, MA, USA (2023)
Todorova, M.; Surendralal, S.; Deißenbeck, F.; Wippermann, S. M.; Neugebauer, J.: Insights into Electrified Solid/Liquid Interfaces from Ab initio and Atomistic Molecular Dynamics Simulations. CECAM - Young Researchers' School on Theory and Simulation in Electrochemical Conversion Processes, Paris, France (2023)
Neugebauer, J.: Current problems in Materials Sciences. New Mathematics for the Exascale: Applications to Materials Science Tutorials, Los Angeles, CA, USA (2023)
Neugebauer, J.; Yang, J.; Todorova, M.; Hickel, T.: Constructing Defect Phase Diagrams from Ab Initio Calculations and CALPHAD Concepts. TMS Annual Meeting and Exhibition, San Diego, CA, USA (2023)
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
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science