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)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
International research team shows how hydrogen affects Nickel-base superalloys at elevated temperatures. Latest results published in journal Nature Materials.
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
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