Chauniyal, A.; Dehm, G.; Janisch, R.: On the role of pre-existing defects in influencing hardness in nanoscale indentations — Insights from atomistic simulations. Journal of the Mechanics and Physics of Solids 154, 104511 (2021)
Cautaerts, N.; Rauch, E. F.; Jeong, J.; Dehm, G.; Liebscher, C.: Investigation of the orientation relationship between nano-sized G-phase precipitates and austenite with scanning nano-beam electron diffraction using a pixelated detector. Scripta Materialia 201, 113930 (2021)
Duarte, M. J.; Fang, X.; Rao, J.; Krieger, W.; Brinckmann, S.; Dehm, G.: In situ nanoindentation during electrochemical hydrogen charging: a comparison between front-side and a novel back-side charging approach. Journal of Materials Science 56 (14), pp. 8732 - 8744 (2021)
Tian, C.; Dehm, G.; Kirchlechner, C.: Influence of strain rate on the activation of {110}, {112}, {123} slip in ferrite of DP800. Materialia 15, 100983 (2021)
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.