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)
Polymeros, G.: Performance of catalysts in electrode structure – bridging the gap between fundamental catalyst properties and behavior in real applications. Dissertation, Ruhr-Universität Bochum, Fakultät für Maschinenbau, Bochum, Germany (2017)
Frenznick, S.: In-situ Untersuchungen zu Benetzungsverhalten und Grenzflächenreaktionen beim Feuerverzinken legierter Stähle. Dissertation, Ruhr-Universität-Bochum, Fakultät für Maschinenbau, Bochum, Germany (2009)
Walczak (vorm. Stempniewicz), M.: Release Studies on Mesoporous Microcapsules for New Corrosion Protection Systems. Dissertation, Ruhr-Universität, Fakultät für Maschinenbau, Institut für Werkstoffe, Bochum, Germany (2007)
Rohwerder, M.: Wasserstoff in Metallen: neue Messverfahren zum Nachweis mit hoher räumlicher Auflösung. Habilitation, Ruhr-Universität Bochum, Bochum, Germany (2016)
Rohwerder, M.; Vogerl, A.; Jarosik, A.; Muhr, A.; Norden, M.; Bordignon, M.; Vanden Eynde, X.: Novel Annealing Procedures for Improving Hot Dip Galvanizing of High Strength Steels. (2010)
Rohwerder, M.; Allély, K. O.; Bendick, M.; Altgassen, C.; Conejero, O.; Tomandl, A.; Fernandes, J. S.; Simoes, A.; Chassagne, J.: Self-Healing at Cut-Edge of Coil Coated Galvanized Steel. (2009)
Hübel, K.; Rohwerder, M.; Scheu, C.; Todorova, M.: Organizer of the workshop “Status and Future Challenges in Characterisation of Interfaces for Electrochemical Applications - Part 1” at the MPIE. (2016)
Rohwerder, M.: Symposium X1 - Electron Transfer Reactions at Organic/Metal Interfaces: From Molecular Monolayer Modified Electrodes to Buried Polymer Metal Interfaces. (2006)
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.