Hickel, T.; Freysoldt, C.; Janßen, J.; Wang, N.; Zendegani, A.: High-throughput optimization of finite temperature phase stabilities: Concepts and application. Coffee with Max Planck, virtual seminar organized by the MPIE, Düsseldorf, Germany (2021)
Janßen, J.; Hickel, T.; Neugebauer, J.: pyiron – an integrated development environment for ab initio thermodynamics. AMS Seminar, virtual, Bochum, Germany (2020)
Neugebauer, J.; Lymperakis, L.; Janßen, J.; Huber, L.; Hickel, T.: Modeling crystal growth and materials design in high dimensional chemical and structural configuration spaces. German Conference on Crystal Growth DKT 2020, München/Garching, Germany (2020)
Hickel, T.: Application of Density Functional Theory in the Context of Phase Diagram Modelling. MSIT Winter School on Materials Chemistry, Virtual Event, Castle Ringberg, Tegernsee (2020)
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)
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) 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…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…