Sözen, H. I.; Ener, S.; Maccari, F.; Fayyazi, B.; Gutfleisch, O.; Neugebauer, J.; Hickel, T.: Combined ab initio and experimental screening of phase stabilities in the Ce–Fe–Ti–X system (X=3d and 4d metals). Physical Review Materials 7 (1), 014410 (2023)
Sözen, H. I.; Hickel, T.; Neugebauer, J.: Impact of magnetism on the phase stability of rare-earth based hard magnetic materials. Calphad 68, 101731 (2020)
Hickel, T.; Aydin, U.; Sözen, H. I.; Dutta, B.; Pei, Z.; Neugebauer, J.: Innovative concepts in materials design to boost renewable energies. Seminar of Institute for Innovative Technologies, SRH Berlin University of Applied Sciences, Berlin, Germany (2020)
Sözen, H. I.: Ab initio investigations on the energetics and kinetics of defects in Fe–Al alloys. Master, Ruhr-Universität Bochum, Bochum, Germany (2014)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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…