Dubosq, R.; Schneider, D.; Zhou, X.; Gault, B.; Langelier, B.; Pleše, P.: Bubbles and atom clusters in rock melts: A chicken and egg problem. Journal of Volcanology and Geothermal Research 428, 107574 (2022)
Harrison, P.; Zhou, X.; Das, S. M.; Lhuissier, P.; Liebscher, C.; Herbig, M.; Ludwig, W.; Rauch, E. F.: Reconstructing dual-phase nanometer scale grains within a pearlitic steel tip in 3D through 4D-scanning precession electron diffraction tomography and automated crystal orientation mapping. Ultramicroscopy 238, 113536 (2022)
Kim, S.-H.; Dong, K.; Zhao, H.; El-Zoka, A.; Zhou, X.; Woods, E.; Giuliani, F.; Manke, I.; Raabe, D.; Gault, B.: Understanding the Degradation of a Model Si Anode in a Li-Ion Battery at the Atomic Scale. The Journal of Physical Chemistry Letters 13 (36), pp. 8416 - 8421 (2022)
Rauch, E.; Harrison, P.; Zhou, X.; Herbig, M.; Ludwig, W.; Veron, M.: Correction: Rauch et al. New Features in Crystal Orientation and Phase Mapping for Transmission Electron Microscopy. Symmetry 2021, 13, 1675. Symmetry 13 (12), 2339 (2021)
Rauch, E.; Harrison, P.; Zhou, X.; Herbig, M.; Ludwig, W.; Véron, M.: New Features in Crystal Orientation and Phase Mapping for Transmission Electron Microscopy. Symmetry 13 (9), 1675 (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.
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…