Kanjilal, A.; Aliramaji, S.; Neuß, D.; Hans, M.; Schneider, J. M.; Best, J. P.; Dehm, G.: Microscale deformation of an intermetallic-metal interface in bi-layered film under shear loading. Scripta Materialia 263, 116665 (2025)
Jentner, R.; Scholl, S.; Srivastava, K.; Best, J. P.; Kirchlechner, C.; Dehm, G.: Local strength of bainitic and ferritic HSLA steel constituents understood using correlative electron microscopy and microcompression testing. Materials and Design 236, 112507 (2023)
Jentner, R.; Tsai, S.-P.; Welle, A.; Scholl, S.; Srivastava, K.; Best, J. P.; Kirchlechner, C.; Dehm, G.: Automated classification of granular bainite and polygonal ferrite by electron backscatter diffraction verified through local structural and mechanical analyses. Journal of Materials Research 38 (18), pp. 4177 - 4191 (2023)
Dubosq, R.; Woods, E.; Gault, B.; Best, J. P.: Electron microscope loading and in situ nanoindentation of water ice at cryogenic temperatures. PLoS One 18 (2), e0281703 (2023)
Shi, J.; Ma, S.; Best, J. P.; Stolpe, M.; Wei, S.; Zhang, P.; Markert, B.: Gradient-enhanced modelling of deformation-induced anisotropic damage in metallic glasses. Journal of the Mechanics and Physics of Solids 167, 105020 (2022)
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.