Scheu, C.: Structural and functional properties of Nb3O7(OH) nanoarrays and their modification via doping and thermal annealing. Talk at Institut für Werkstofftechnik, Technische Universität Ilmenau, Ilmenau, Gemany (2017)
Scheu, C.: Interface structure of Kappa-Carbides in high Mn Steels. 3 Phase, Interface, Component Systems (PICS), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), Marseille, France (2017)
Raabe, D.; Gault, B.; Yao, M.; Scheu, C.; Liebscher, C.; Herbig, M.: Correlated and simulated electron microscopy and atom probe tomography. Workshop on Possibilities and Limitations of Quantitative Materials Modeling and Characterization 2017, Bernkastel, Germany (2017)
Scheu, C.: Grain growth and dewetting of thin Al films on (0001) Al2O3 substrates. 3 Phase, Interface, Component Systems (PICS), Centre Interdisciplinaire de Nanoscience de Marseille (CINaM), Marseille, France (accepted)
Scheu, C.: In-situ Transmission Electron Microscopy Observation of Heat-Induced Structural Changes of 3D Nb3O(OH) Networks. Electronic Materials and Applications 2017 (EMA), Orlando, FL, USA (2017)
Scheu, C.: Insights into structural and functional properties of Nb3O7(OH) and TiO2 nanoarrays. European Materials Research Society’s (EMRS) Fall Meeting, Warsaw, Poland (2016)
Scheu, C.: Transmission electron microscopy – a versatile tool to study the microstructure of HT-PEMFC. Materials Science 2016, Atlanta, GA, USA (2016)
Scheu, C.: Insights into structural and functional properties of nano-structured electrodes for energy and fuel generating devices. Talk at Helmholtz‐Zentrum Geesthacht, Geesthacht, Germany (2016)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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.