Su, J.; Li, Z.; Raabe, D.: Microstructural Design to Improve the Mechanical Properties of an Interstitial TRIP-TWIP High-Entropy Alloy. MRS Fall Meeting , Boston, MA, USA (2018)
Niendorf, T.; Wegener, T.; Li, Z.; Raabe, D.: On the fatigue behavior of dual-phase high-entropy alloys in the low-cycle fatigue regime. Fatique 2018, Poitiers, France (2018)
Li, Z.; Raabe, D.: Tuning Phase Transformation in Compositionally Complex Alloys for Superior Mechanical Properties. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Oh, H. S.; Li, Z.; Kim, J. Y.; Ryu, C. W.; Meyer, A.; Tsuchiya, K.; Raabe, D.; Park, E. S.: Phase Stabilization of High Entropy Alloy under Dynamic Forcing Condition. TMS 2018 Annual Meeting & Exhibition, Phoenix, AZ, USA (2018)
Li, Z.; Raabe, D.: Designing novel high-entropy alloys towards superior properties. Frontiers in Materials Processing Applications, Research and Technology (FiMPART'2017), Bordeaux, France (2017)
Li, Z.: Designing and understanding novel high-entropy alloys towards superior properties. Talk at Universität Kassel, Institut für Werkstofftechnik, Kassel, Germany (2017)
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.