Stein, F.: Experimental Determination of Phase Diagrams. Lecture: Lecture at the 3rd MSIT Winter School on Materials Chemistry, Castle Ringberg, Tegernsee, March 04, 2019 - March 07, 2019
Stein, F.: Experimental Determination of Phase Diagrams. Lecture: 6th APDIC World Round Robin Seminar, 2nd MSIT Winter School on Materials Chemistry, Schloss Ringberg, Tegernsee, Germany, February 11, 2018 - February 14, 2018
Stein, F.: Phase Diagrams – Why You Need Them, How You Can Use Them, and How You Can Generate Them. Lecture: MPIE lecture series, Düsseldorf, Germany, February 06, 2017
Palm, M.; Stein, F.; Pyczak, F.: Co-organization and co-chair the priority topic “Hochtemperaturwerkstoffe“ (high temperature materials) at the 62. Metallkunde Kolloquium. (2016)
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…
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…
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…