Gomell, L.: Advancing the understanding of the microstructure-property relationship in non-toxic and cost-effective thermoelectric Heusler compounds. Dissertation, Fakultät für Georessourcen und Materialtechnik der RWTH Aachen, Germany (2022)
Yilmaz, C.: Influence of Processing Parameters, Crystallography and Chemistry of Defects on the Microstructure and Texture Evolution in Grain-Oriented Electrical Steels. Dissertation, RWTH Aachen, Germany (2022)
Prithiv, T. S.: Grain boundary segregation of boron and carbon and their local chemical effects on the phase transformations in steels. Dissertation, Faculty of Georesources and Materials Engineering of the RWTH Aachen, Germany (2021)
Mayweg, D.: Microstructural characterization of white etching cracks in 100Cr6 bearing steel with emphasis on the role of carbon. Dissertation, RWTH Aachen University (2021)
Schweinar, K.: Advancements in the understanding of Ir-based water splitting catalysts at the near-atomic scale. Dissertation, Ruhr-Universität Bochum (2021)
Varanasi, R. S.: Mechanisms of refinement and deformation of novel ultrafine-grained medium manganese steels with improved mechanical properties. Dissertation, Ruhr-Universität Bochum (2021)
Keuter, P.: Design of materials with anomalous thermophysical properties and desorption-assisted phase formation of intermetallic thin films. Dissertation, RWTH Aachen University (2020)
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
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…
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.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…