Ma, Y.; Villanova, J.; Requena, G.; Raabe, D.: Understanding the physical-chemical phenomena in green steel production using synchrotron X-ray techniques. European Synchrotron Radiation Facility User Meeting 2022, Online (2022)
Ma, Y.; Zaefferer, S.; Raabe, D.: Hydrogen-based direct reduction of iron ores: Microstructure, crystallography, and reduction mechanisms. 2021 International Metallurgical Processes Workshop for Young Scholars (IMPROWYS2021), a hybrid event, Online (2021)
Ma, Y.: Materials Characterization – Introduction to X-ray Diffraction. Lecture: International Max Planck Research School for Interface Controlled Materials for Energy Conversion (IMPRSURMAT), online, 2021-08
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) 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…
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.