Hickel, T.; McEniry, E.; Nazarov, R.; Dey, P.: Ab initio basierte Simulation zur Wasserstoffversprödung in hoch-Mn Stählen. Seminar der Staatlichen Materialprüfungsanstalt Darmstadt, Institut für Werkstoffkunde, Darmstadt, Germany (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)
Janßen, J.; Hickel, T.; Neugebauer, J.: Automated ab-initio Determination of Materials Properties at finite Temperatures with pyiron. CNLS Seminar, Los Alamos, NM, USA (2019)
Neugebauer, J.; Huber, L.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio input for multiphysics models: Accuracy, performance and challenges. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Erlangen, Germany (2019)
Tehranchi, A.; Hickel, T.; Neugebauer, J.: Atomistic simulations of hydrogen-defect interactions in metals. Workshop "Hydrogen in Metals - current understanding and future needs", St Anne's College, Oxford, UK (2019)
Neugebauer, J.; Todorova, M.; Grabowski, B.; Hickel, T.: Modelling structural materials in realistic environments by ab initio thermodynamics. Hume-Rothery Award Symposium, TMS2019 Annual Meeting and Exhibition, San Antonio, TX, USA (2019)
Hickel, T.: Application of Density Functional Theory in the Context of Phase Diagram Modelling. MSIT Winter School on Materials Chemistry, Castle Ringberg, Tegernsee (2019)
Hickel, T.; Zendegani, A.; Körmann, F.; Neugebauer, J.: Energetics of non-stoichiometric stacking faults in Fe–Nb alloys: An ab initio study. TMS 2019 Annual Meeting, San Antonio, TX, USA (2019)
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…