Race, C. P.; von Pezold, J.; Neugebauer, J.: Simulations of grain boundary migration via the nucleation and growth of islands. DPG Frühjahrstagung 2012, Berlin, Germany (2012)
Grabowski, B.; Söderlind, P.; Hickel, T.; Neugebauer, J.: Ab Initio Thermodynamics of the fcc-bcc Transition in Ca Including All Relevant FiniteTemperature Excitation Mechanisms. TMS 2012, Orlando, FL, USA (2012)
Nazarov, R.; Hickel, T.; Neugebauer, J.: Accelerated self-diffusion in fcc metals due to H induced superabundant vacancies. TMS 2012 Meeting, Orlando, FL, USA (2012)
Neugebauer, J.: Long time scale simulations to determine accurate ab initio free energies. Beyond Molecular Dynamics (BEMOD) workshop, Dresden, Germany (2012)
Nazarov, R.; Hickel, T.; Neugebauer, J.: Influence of alloying elements on solubility and diffusivity of H in different steel phases. HYDRAMYCROS Workshop, Ghent, Belgium (2012)
von Pezold, J.; Lymperakis, L.; Neugebauer, J.: Towards an ab-initio based understanding of H-embrittlement: An atomistic study of the HELP mechanism. Joint Hydrogenius and ICNER International Workshop on Hydrogen-Materials Interactions, Kyushu, Japan (2012)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…