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)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…