Sobota, L.; Bondue, C. J.; Hosseini, P.; Kaiser, C.; Spallek, M.; Tschulik, K.: Impact of the Electrochemically Inert Furan Ring on the Oxidation of the Alcohol and Aldehyde Functional Group of 5-Hydroxymethylfurfural (HMF). ChemElectroChem 11 (1), e202300151 (2024)
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)
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
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
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…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…