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)
Neugebauer, J.; Yoo, S.-H.; Lymperakis, L.: Ab initio insights into fundamental intrinsic growth and materials limitations in group-III-nitrides. MRS 2021 Fall Meeting, Virtual Conference, Boston, MA, USA (2021)
Janßen, J.; Hickel, T.; Neugebauer, J.: pyiron – an integrated development environment for ab initio thermodynamics. AMS Seminar, virtual, Bochum, Germany (2020)
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
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
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.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…