Krieg, R.; Vimalanandan, A.; Rohwerder, M.: Corrosion of Zinc and Zn–Mg Alloys with Varying Microstructures and Magnesium Contents. Journal of the Electrochemical Society 161 (3), pp. C156 - C161 (2014)
Krieg, R.; Vimalanandan, A.; Rohwerder, M.; Theirry, D.; Le Bozec, N.: Corrosion Performance of Zinc Magnesium Aluminium Coated steel: Discussion of fundamental mechanisms. 224th ECS Meeting, San Francisco, CA, USA (2013)
Palm, M.; Krieg, R.: Neutral salt spray tests on Fe−Al and Fe−Al−X. FeAl2011, Discussion Meeting on the Development of Innovative Iron Aluminium Alloys, Lanzarote, Canary Islands, Spain (2011)
Krieg, R.: Untersuchungen zur Inhibition der Sauerstoffreduktion durch Zink-basierende Korrosionsproduktschichten. Dissertation, Fakultät für Chemie und Biochemie, Ruhr-Universität Bochum, Bochum, Germany (2013)
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.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…