Saveleva, V. A.; Wang, L.; Kasian, O.; Batuk, M.; Hadermann, J.; Gallet, J.-J.; Bournel, F.; Alonso-Vante, N.; Ozouf, G.; Beauger, C.et al.; Mayrhofer, K. J. J.; Cherevko, S.; Gago, A. S.; Friedrich, K. A.; Zafeiratos, S.; Savinova, E. R.: Insight into the Mechanisms of High Activity and Stability of Iridium Supported on Antimony-Doped Tin Oxide Aerogel for Anodes of Proton Exchange Membrane Water Electrolyzers. ACS Catalysis 10 (4), pp. 2508 - 2516 (2020)
Shkirskiy, V.; Speck, F. D.; Kulyk, N.; Cherevko, S.: On the time resolution of electrochemical scanning flow cell coupled to downstream analysis. Journal of the Electrochemical Society 166 (16), pp. H866 - H870 (2019)
Kasian, O.; Grote, J.-P.; Geiger, S.; Cherevko, S.; Mayrhofer, K. J. J.: The Common Intermediates of Oxygen Evolution and Dissolution Reactions during Water Electrolysis on Iridium. Angewandte Chemie International Edition 57 (9), pp. 2488 - 2491 (2018)
Cherevko, S.: Stability and dissolution of electrocatalysts: Building the bridge between model and “real world” systems. Current Opinion in Electrochemistry 8, pp. 118 - 125 (2018)
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
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.