Neugebauer, J.: Efficient sampling of high-dimensional chemical and thermodynamic configuration spaces. ELRC2020: Invitation to Complex High-Dimensional Energy Landscapes Reunion Conference II, Delivered online, Lake Arrowhead, CA, USA (2021)
Neugebauer, J.; Zendegani, A.; Hickel, T.: Defect phase diagrams as novel tool to understand and design tailored defect structures in advanced steels. Thermec2021, Virtual Meeting, Vienna, Austria (2021)
Todorova, M.; Surendralal, S.; Wippermann, S. M.; Deißenbeck, F.; Neugebauer, J.: Insights into processes at electrochemical solid/liquid interfaces from ab initio molecular dynamics simulations. ICTP-Workshop on “Physics and Chemistry of Solid/Liquid Interfaces for Energy Conversion and Storage”, Virtual Meeting, Trieste, Italy (2021)
Neugebauer, J.: Materials design by exploiting high-dimensional chemical and structural configuration spaces. Kolloquium im Rahmen des SFB 986, Technische Universität Hamburg-Harburg, Online Meeting, Hamburg-Harburg, Germany (2021)
Janßen, J.; Hickel, T.; Neugebauer, J.: pyiron – an integrated development environment for ab initio thermodynamics. Potential Workshop, ICAMS, virtual, Bochum, Germany (2021)
Neugebauer, J.; Ikeda, Y.; Körmann, F.: Materials design based on efficient sampling of high dimensional chemical and thermodynamic configuration spaces. Workflows for Atomistic Simulations, Ruhr-Universität Bochum, Online Meeting, Bochum, Germany (2021)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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