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)
Tan, A. M. Z.; Freysoldt, C.; Hennig, R. G.: First-principles investigation of charged dopants and dopant-vacancy defect complexes in monolayer MoS2. Physical Review Materials 4 (11), 114002 (2020)
Tan, A. M. Z.; Freysoldt, C.; Hennig, R. G.: Stability of charged sulfur vacancies in 2D and bulk MoS2 from plane-wave density functional theory with electrostatic corrections. Physical Review Materials 4 (6), 064004 (2020)
Freysoldt, C.; Neugebauer, J.: First-principles calculations for charged defects at surfaces, interfaces, and two-dimensional materials in the presence of electric fields. Physical Review B 97 (20), 205425 (2018)
Wang, J.; Freysoldt, C.; Du, Y.; Sun, L.: First-Principles study of intrinsic defects in ammonia borane. The Journal of Physical Chemistry C 121 (41), pp. 22680 - 22689 (2017)
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
Water electrolysis has the potential to become the major technology for the production of the high amount of green hydrogen that is necessary for its widespread application in a decarbonized economy. The bottleneck of this electrochemical reaction is the anodic partial reaction, the oxygen evolution reaction (OER), which is sluggish and hence…