Rabe, M.; Toparli, C.; Chen, Y.-H.; Kasian, O.; Mayrhofer, K. J. J.; Erbe, A.: Alkaline manganese electrochemistry studied by in situ and operando spectroscopic methods - metal dissolution, oxide formation and oxygen evolution. Physical Chemistry Chemical Physics 21 (20), pp. 10457 - 10469 (2019)
Toparli, C.; Ebin, B.; Gürmen, S.: Synthesis, structural and magnetic characterization of soft magnetic nanocrystalline ternary FeNiCo particles. Journal of Magnetism and Magnetic Materials 423, pp. 133 - 139 (2017)
Toparli, C.; Sarfraz, A.; Erbe, A.: A new look at oxide formation at the copper/electrolyte interface by in situ spectroscopies. Physical Chemistry Chemical Physics 17, pp. 31670 - 31679 (2015)
Erbe, A.; Nayak, S.; Chen, Y.-H.; Niu, F.; Pander, M.; Tecklenburg, S.; Toparli, C.: How to probe structure, kinetics and dynamics at complex interfaces in situ and operando by optical spectroscopy. In: Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry; part of "Reference Module in Chemistry, Molecular Sciences and Chemical Engineering", pp. 199 - 219 (Ed. Wandelt, K.). Elsevier, Waltham, MA, USA (2017)
Toparli, C.: Passivity and passivity breakdown on copper: In situ and operando observation of surface oxides. Dissertation, Ruhr-Universität Bochum, Fakultät Maschinenbau, Bochum, Germany (2017)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
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.