Liebscher, C.; Leitherer, A.; Chul Yeo, B.; Freysoldt, C.; Ghiringhelli, L. M.: Unsupervised and supervised machine learning for feature classification in atomic resolution images. BIO Web of Conferences 129, 10023 (2024)
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)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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…