Saksena, A.; Sun, B.; Dong, X.; Khanchandani, H.; Ponge, D.; Gault, B.: Optimizing site-specific specimen preparation for atom probe tomography by using hydrogen for visualizing radiation-induced damage. International Journal of Hydrogen Energy 50 (Part A), pp. 165 - 174 (2024)
Saksena, A.; Kubacka, D.; Gault, B.; Spieker, E.; Kontis, P.: The effect of γ matrix channel width on the compositional evolution in a multi-component nickel-based superalloy. Scripta Materialia 219, 114853 (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
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…
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…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.