Li, Y.; Gault, B.: Machine Learning-enabled Tomographic Imaging of Chemical Short-range Order in Fe-based Solid-solutions. DPG 2024, Berlin, Germany (2024)
Li, Y.; Gault, B.: Machine Learning-enabled Tomographic Imaging of Chemical Short-range Order in Fe-based Solid-solutions. TMS 2024, Orlando, FL, USA (2024)
Li, Y.; Gault, B.: Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography. BiGmax Spring Meeting 2022, Bochum, Germany (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
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.