Vogel, S. C.; Eumann, M.; Palm, M.; Stein, F.: Investigation of the crystallographic structure of the ε phase in the Fe–Al system by high-temperature neutron diffraction. TMS 2009 Annual Meeting, San Francisco, CA, USA (2009)
Stein, F.: The Binary Fe–Al System. 5th Discussion Meeting on the Development of Innovative Iron Aluminium Alloys (FEAL 2009), Prague, Czech Republic (2009)
Kumar, K. S.; Stein, F.; Palm, M.: An in-situ electron microscopy study of microstructural evolution in a Co–Co2Nb binary alloy. MRS Fall Meeting 2008, Boston, MA, USA (2008)
Vogel, S. C.; Eumann, M.; Palm, M.; Stein, F.: Investigation of the crystallographic structure of the ε phase in the Fe–Al system by high-temperature neutron diffraction. 20th Annual Rio Grande Symposium on Advanced Materials 2008, Albuquerque, NM, USA (2008)
Kumar, K. S.; Stein, F.; Palm, M.: Preliminary in-situ TEM observations of phase transformations in a Co–15 at.% Nb alloy. Workshop "The Nature of Laves Phases XI", MPIE Düsseldorf, Germany (2008)
Prymak, O.; Stein, F.: Composition dependence of site occupancy and c/a ratio in hexagonal C14 Laves phase of the Nb–Cr–Al system. TOFA Thermodynamics of Alloys 2008, Krakow, Poland (2008)
Stein, F.; Ishikawa, S.; Takeyama, M.; Kumar, K. S.; Palm, M.: Phase equilibria in the Cr–Ti system studied by diffusion couples and equilibrated two-phase alloys. Workshop "The Nature of Laves Phases XI", MPI für Eisenforschung, Düsseldorf, Germany (2008)
Stein, F.; Prymak, O.; Dovbenko, O. I.; Palm, M.: Phase equilibria of Laves phases in ternary Nb–X–Al systems with X = Cr, Fe, Co. Discussion Meeting on Thermodynamics of Alloys - TOFA 2008, Krakow, Poland (2008)
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.
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…