Neugebauer, J.; Yang, J.; Todorova, M.; Hickel, T.: Constructing Defect Phase Diagrams from Ab Initio Calculations and CALPHAD Concepts. TMS Annual Meeting and Exhibition, San Diego, CA, USA (2023)
Neugebauer, J.; Körmann, F.; Hickel, T.: Ab Initio Descriptors to Guide Materials Design in High-dimensional Chemical and Structural Configuration Spaces. TMS Annual Meeting and Exhibition, San Diego, CA, USA (2022)
Neugebauer, J.; Zendegani, A.; Hickel, T.: Construction and Application of Defect Phase Diagrams. TMS Annual Meeting and Exhibition, Anaheim, CA, USA (2022)
Neugebauer, J.; Zendegani, A.; Hickel, T.: Defect phase diagrams as novel tool to understand and design tailored defect structures in advanced steels. Thermec2021, Virtual Meeting, Vienna, Austria (2021)
Hickel, T.: Application of Density Functional Theory in the Context of Phase Diagram Modelling. MSIT Winter School on Materials Chemistry, Virtual Event (2021)
Janßen, J.; Hickel, T.; Neugebauer, J.: pyiron – an integrated development environment for ab initio thermodynamics. Potential Workshop, ICAMS, virtual, Bochum, Germany (2021)
Freysoldt, C.; Hickel, T.; 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)
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)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
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.