Hieke, S. W.; Breitbach, B.; Dehm, G.; Scheu, C.: Microstructural evolution and solid state dewetting of epitaxial Al thin films on sapphire (α-Al2O3). Acta Materialia 133, pp. 356 - 366 (2017)
Malyar, N.; Micha, J.-S.; Dehm, G.; Kirchlechner, C.: Dislocation-twin boundary interaction in small scale Cu bi-crystals loaded in different crystallographic directions. Acta Materialia 129, pp. 91 - 97 (2017)
Peter, N. J.; Liebscher, C.; Kirchlechner, C.; Dehm, G.: Beam-induced atomic migration at Ag-containing nanofacets at an asymmetric Cu grain boundary. Journal of Materials Research 32 (5), pp. 968 - 982 (2017)
Harzer, T. P.; Duarte, M. J.; Dehm, G.: In–situ TEM study of diffusion kinetics and electron irradiation effects on the Cr phase separation of a nanocrystalline Cu–4 at.% Cr thin film alloy. Journal of Alloys and Compounds 695, pp. 1583 - 1590 (2017)
Harzer, T. P.; Dehm, G.: Stability, phase separation and oxidation of a supersaturated nanocrystalline Cu–33 at.% Cr thin film alloy. Thin Solid Films 623, pp. 48 - 58 (2017)
Brinckmann, S.; Kirchlechner, C.; Dehm, G.: Stress intensity factor dependence on anisotropy and geometry during micro-fracture experiments. Scripta Materialia 127, pp. 76 - 78 (2017)
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…