Kawano, T.; Renner, F. U.: Studies on Wetting Behaviour of Hot-dip Galvanizing Process by use of Model Specimens with Tailored Surface Oxides. Surf. Int. Anal. 44 (8), pp. 1009 - 1012 (2012)
Kawano, T.; Renner, F. U.: Tailoring Model Surface and Wetting Experiment for a Fundamental Understanding of Hot-dip Galvanizing. ISIJ International 51, 10, pp. 1703 - 1709 (2011)
Kawano, T.; Renner, F. U.: Tailoring Model Surfaces and Wettability Measurement for a Fundamental Understanding of Hot-dip Galvanizing. DPG Meeting, Regensburg, Germany (2010)
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
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.