Cherevko, S.; Geiger, S.; Kasian, O.; Mingers, A. M.; Mayrhofer, K. J. J.: Oxygen evolution activity and stability of iridium in acidic media. Part 2. – Electrochemically Grown Hydrous Iridium Oxide. Journal of Electroanalytical Chemistry 774, pp. 102 - 110 (2016)
Ledendecker, M.; Mondschein, J. S.; Žeradjanin, A. R.; Cherevko, S.; Geiger, S.; Schalenbach, M.; Schaak, R. E.; Mayrhofer, K. J. J.: Stability of binary metallic ceramics in the HER reaction - feasible HER electrocatalysts in acidic medium? In Abstracts of Papers of the American Chemical Society, 254, 350. 254th National Meeting and Exposition of the American-Chemical-Society
(ACS) on Chemistry's Impact on the Global Economy, Washington, DC, August 20, 2017 - August 24, 2017. (2017)
Geiger, S.; Cherevko, S.; Mayrhofer, K. J. J.: Platinum dissolution in presence of chlorides. 3rd Ertl Symposium on Surface Analysis and Dynamics
, Berlin, Germany (2014)
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
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
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.