Changizi, R.: Structural Analysis and Correlative Cathodoluminescence Investigations of Pr (doped) Niobates. Dissertation, Georessourcen und Materialtechnik, RWTH Aachen (2022)
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)
Abdellaoui, L.: Correlation of microstructures and thermal conductivity of the thermoelectric material Ag16.7Sb30Te53.3. Dissertation, Ruhr-Universität Bochum (2019)
Sysoltseva, M.: Characterization of aerosols and nanoparticles released during various indoor and outdoor human activities. Dissertation, RWTH Aachen University (2018)
Folger, A.: The Influence of Post-Growth Heat Treatments and Etching on the Nanostructure and Properties of Rutile TiO2 Nanowires. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Gleich, S.: Investigation of Sputtered Mo2BC Hard Coatings: Correlation of Nanostructure and Mechanical Properties. Dissertation, RWTH Aachen, Aachen, 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
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.
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…