Sandlöbes, S.; Friák, M.; Dick, A.; Zaefferer, S.; Pei, Z.; Zhu, L.-F.; Sha, G.; Ringer, S.; Neugebauer, J.; Raabe, D.: Combining ab initio calculations and high resolution experiments to improve the understanding of advanced Mg-Y and Mg-RE alloys. 7th Annual Conference of the ARC Centre of Excellence for Design in Light Metals, Melbourne, VIC, Australia (2012)
Sandlöbes, S.; Friák, M.; Dick, A.; Zaefferer, S.; Pei, Z.; Neugebauer, J.; Raabe, D.: Combining ab initio calculations and high-resolution experiments to understand advanced Mg alloys. German-Korean workshop on the “Production and industrial applications of semi-finished Mg products”, Irsee, Germany (2011)
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.