Cherevko, S.; Keeley, G. P.; Kulyk, N.; Mayrhofer, K. J. J.: Pt Sub-Monolayer on Au: System Stability and Insights into Platinum Electrochemical Dissolution. Journal of the Electrochemical Society 163 (3), pp. H228 - H233 (2016)
Keeley, G. P.; Cherevko, S.; Mayrhofer, K. J. J.: The Stability Challenge on the Pathway to Low and Ultra-Low Platinum Loading for Oxygen Reduction in Fuel Cells. ChemElectroChem 3 (1), pp. 51 - 54 (2016)
Reier, T.; Pawolek, Z.; Cherevko, S.; Bruns, M.; Jones, T.; Teschner, D.; Selve, S.; Bergmann, A.; Nong, H. N.; Schloegl, R.et al.; Mayrhofer, K. J. J.; Strasser, P.: Molecular Insight in Structure and Activity of Highly Efficient, Low-Ir Ir-Ni Oxide Catalysts for Electrochemical Water Splitting (OER). Journal of the American Chemical Society 137 (40), pp. 13031 - 13040 (2015)
Žeradjanin, A. R.; Topalov, A. A.; Cherevko, S.; Keeley, G. P.: Sustainable generation of hydrogen using chemicals with regional oversupply - Feasibility of the electrolysis in acido-alkaline reactor. International Journal of Hydrogen Energy 39 (29), pp. 16275 - 16281 (2014)
Grote, J.-P.; Žeradjanin, A. R.; Cherevko, S.; Mayrhofer, K. J. J.: Coupling of a scanning flow cell with online electrochemical mass spectrometry for screening of reaction selectivity. Review of Scientific Instruments 85 (10), 104101 (2014)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…