Lee, J. S.; Riedel, J. L.; Schweizer, P.; Kauffmann, A.; Heilmaier, M.; Dehm, G.; Best, J. P.; Kanjilal, A.; Stein, F.: Influence of point defects on the hardness and reduced modulus of B2-ordered FeAl. Journal of Alloys and Compounds 1065, 188036 (2026)
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)
Best, J. P.; Gibson, J. S. K. L.; Lawrence, S.; Lee, S.; Lee, S.-W.: Nanoindentation's imprint on an advanced society: Toward application conditions at the extremes. MRS Bulletin 50 (6), pp. 695 - 704 (2025)
Dubosq, R.; Woods, E.; Gault, B.; Best, J. P.: Correction: Electron microscope loading and in situ nanoindentation of water ice at cryogenic temperatures. PLOS ONE 19 (6), e0306374 (2024)
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)
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.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…