Raabe, D.: The role of texture and anisotropy in nano- and microscale materials mechanics. Keynote lecture at the Plasticity Conference 2004/2005, Hawai, USA (2005)
Raabe, D.: Using the Lattice Boltzmann Method for Multiscale Modeling in Materials Science and Engineering. Lecture at the Plasticity Conference 2004/2005, Hawai, USA (2005)
Raabe, D.; Romano, P.; Al-Sawalmih, A.; Sachs, C.; Servos, G.; Hartwig, H. G.: Microstructure and Mesostructure of the exoskeleton of the lobster homarus americanus. MRS Spring Meeting, San Francisco, CA, USA (2005)
Raabe, D.; Roters, F.: How do 10^10 crystals co-deform. "Weitab vom Hooksechen Gesetz -- Moderne Ansätze und Ingenieurpraxis großer inelastischer deformation metallischer Werkstoffe'' Symposium der Akademie der Wissenschaften und der Literatur, Mainz, Germany (2004)
Raabe, D.; Roters, F.: Physically-Based Large-Scale Texture and Anisotropy Simulation for Automotive Sheet Forming. TMS Fall meeting, New Orleans, LA, USA (2004)
Konrad, J.; Raabe, D.; Zaefferer, S.: Investigation of Nucleation Mechanisms of Recrystallization in Warm Rolled Fe3Al Base Alloys. 2nd International Conference on Recrystallization and Grain Growth, Annecy, France (2004)
Raabe, D.: Recrystallization in Polymers – Experiments and Simulations. Invited Keynote lecture, 2nd International Conference on Recrystallization and Grain Growth, REX&GG 2004 Annecy, Annecy, France (2004)
Raabe, D.: Textures and Micromechanics in Experiment and Theory on Metals and Semi-Crystalline Polymers. Joint Colloquium of the University of Vienna and Technical University of Vienna, Vienna (2004)
Raabe, D.: Simulations and Experiments on Micromechanics in Metals and Polymers. Colloquium lecture at the Department for Theoretical Physics, University of Paderborn (2004)
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…