Nazarov, R.; Hickel, T.; Neugebauer, J.: Ab initio study of H-vacancy interactions in fcc metals: Implications for the formation of superabundant vacancies. Physical Review B 89 (14), 144108 (2014)
Glensk, A.; Grabowski, B.; Hickel, T.; Neugebauer, J.: Breakdown of the Arrhenius law in describing vacancy formation energies: The importance of local anharmonicity revealed by Ab initio thermodynamics. Physical Review X 4 (1), 011018 (2014)
Neugebauer, J.; Hickel, T.: Density functional theory in materials science. Wiley Interdisciplinary Reviews-Computational Molecular Science 3 (5), pp. 438 - 448 (2013)
Ouyang, Y.; Tong, X.; Li, C.; Chen, H.; Tao, X.; Hickel, T.; Du, Y.: Thermodynamic and physical properties of FeAl and Fe3Al: An atomistic study by EAM simulation. Physica B-Condensed Matter 407 (23), pp. 4350 - 4536 (2012)
Schick, M.; Hallstedt, B.; Glensk, A.; Grabowski, B.; Hickel, T.; Hampl, M.; Gröbner, J.; Neugebauer, J.; Schmid-Fetzer, R.: Combined ab initio, experimental, and CALPHAD approach for an improved thermodynamic evaluation of the Mg–Si system. Calphad: Computer Coupling of Phase Diagrams and Thermochemistry 37, pp. 77 - 86 (2012)
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
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.