Freysoldt, C.; Neugebauer, J.; Tan, A. M. Z.; Hennig, R. G.: Limitations of empirical supercell extrapolation for calculations of point defects in bulk, at surfaces, and in two-dimensional materials. Physical Review B 105 (1), 014103 (2022)
Kavanagh, S. R.; Scanlon, D. O.; Walsh, A.; Freysoldt, C.: Impact of metastable defect structures on carrier recombination in solar cells. Faraday Discussions 239, pp. 339 - 356 (2022)
Wang, N.; Freysoldt, C.; Zhang, S.; Liebscher, C.; Neugebauer, J.: Segmentation of Static and Dynamic Atomic-Resolution Microscopy Data Sets with Unsupervised Machine Learning Using Local Symmetry Descriptors. Microscopy and Microanalysis 27 (6), pp. 1454 - 1464 (2021)
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.