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)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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
The project Hydrogen Embrittlement Protection Coating (HEPCO) addresses the critical aspects of hydrogen permeation and embrittlement by developing novel strategies for coating and characterizing hydrogen permeation barrier layers for valves and pumps used for hydrogen storage and transport applications.