Luan, C.; Corva, M.; Hagemann, U.; Wang, H.; Heidelmann, M.; Tschulik, K.; Li, T.: Atomic-Scale Insights into Morphological, Structural, and Compositional Evolution of CoOOH during Oxygen Evolution Reaction. ACS Catalysis 13 (2), pp. 1400 - 1411 (2023)
Piontek, S. M.; Naujoks, D.; Tabassum, T.; DelloStritto, M. J.; Jaugstetter, M.; Hosseini, P.; Corva, M.; Ludwig, Alfred, A.; Tschulik, K.; Klein, M. L.et al.; Petersen, P. B.: Probing the Gold/Water Interface with Surface-Specific Spectroscopy. ACS Physical Chemistry Au 3 (1), pp. 119 - 129 (2023)
Kanokkanchana, K.; Tschulik, K.: Electronic Circuit Simulations as a Tool to Understand Distorted Signals in Single-Entity Electrochemistry. The Journal of Physical Chemistry Letters 13 (43), pp. 10120 - 10125 (2022)
Corva, M.; Blanc, N.; Bondue, C. J.; Tschulik, K.: Differential Tafel Analysis: A Quick and Robust Tool to Inspect and Benchmark Charge Transfer in Electrocatalysis. ACS Catalysis 12, pp. 13805 - 13812 (2022)
Rurainsky, C.; Nettler, D. -.; Pahl, T.; Just, A.; Cignoni, P.; Kanokkanchana, K.; Tschulik, K.: Electrochemical dealloying in a magnetic field-Tapping the potential for catalyst and material design. Electrochimica Acta 426, 140807 (2022)
Aymerich Armengol, R.; Cignoni, P.; Ebbinghaus, P.; Linnemann, J.; Rabe, M.; Tschulik, K.; Scheu, C.; Lim, J.: Electron microscopy insights on the mechanism of morphology/phase transformations in manganese oxides. Institut de Nanociència i Nanotecnologia (ICN2), Bellaterra, Spain (2022)
Aymerich Armengol, R.; Cignoni, P.; Ebbinghaus, P.; Rabe, M.; Tschulik, K.; Scheu, C.; Lim, J.: Mechanism of coupled phase/morphology transformation of 2D manganese oxides through Fe galvanic exchange reaction. Chemistry Department Seminar, Kangwon National University, Chuncheon, South Korea (2022)
Ceremony on 16 April with the Minister for Culture and Science of North Rhine-Westphalia, Ina Brandes, the Lord Mayor of Düsseldorf, Stephan Keller, and the President of the Max Planck Society, Patrick Cramer
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