Dumont, M.; Borbély, A.; Sander, P. M.; Kostka, A.; Kaysser-Pyzalla, A. R.: Crystallographic investigations of a growth series of Apatosaurus long bones: Implications for biomechanics. 71st SVP meeting, Las Vegas, NV, USA (2011)
Dumont, M.; Borbély, A.; Sander, P. M.; Kostka, A.; Kaysser-Pyzalla, A. R.: Texture and nanostructure of Sauropod bones: Implications for biomechanics. 1st International symposium on paleohistology, Barcelona, Spain (2011)
Dumont, M.; Kostka, A.; Sander, M.; Borbély, A.; Pyzalla, A. R.: Comparison of apatite crystallite sizes in sauropod and mammal fossil bones. 6th Bone diagenesis meeting, Poppelsdorfer Schloss, University of Bonn, Germany (2009)
Barbatti, C.; Pinto, H.; Pyzalla, A. R.: Defect and Stress Analyses in Novel Fe-Mn-C Steels by X-Ray Diffraction. MSE08 Materials Science and Engineering, Nürnberg, Germany (2008)
Brito, P.; Pinto, H.; Genzel, C.; Pyzalla, A. R.: Phase Composition and Internal Stress Development during the Oxidation of Iron Aluminides. MSE08 Materials Science and Engineering, Nürnberg, Germany (2008)
Garcia, J.; Pyzalla, A. R.: Experimental Investigations on the Influence of (Ta,Nb)C and Processing Parameters on the Formation of Wear Resistant Graded Surfaces in Cemented Carbides. MSE08 Materials Science and Engineering, Nürnberg, Germany (2008)
Moscicki, M.; Pinto, H.; Paulmann, C.; Borbély, A.; Pyzalla, A. R.: In-Situ Investigation of Grain Rotations During Tensile Straining of Steel Wires. MSE08 Materials Science and Engineering, Nürnberg, Germany (2008)
Pyzalla, A. R.; Dumont, M.; Zoeger, N.; Streli, C.; Wobrauscheck, P.; Sander, M.: Synchrotron XRF analyses of element distribution in fossilized sauropod dinosaur bones. Denver X-ray Conference, Denver (2008)
Guio, A.; Pinto, H.; Pyzalla, A. R.; Jahn, A.; Standfuß, J.: Characterization of induction assisted welds in high strength steel grades. 2nd International Conference on Steels in Cars and Trucks 2008, Wiesbaden, Germany (2008)
Guio, A.; Pinto, H.; Garcia, J.; Jahn, A.; Standfuß, J.; Pyzalla, A. R.: Characterization of Induction-Assisted Welds in High Strength Steel Grades. Steel Conference 2008 - New Developments on Metallurgy and Applications of High Strength Steels, Buenos Aires, Argentina (2008)
Coelho, R. S.; Kostka, A.; Sheikhi, S.; Kocak, M.; Dos Santos, J.; Pyzalla, A. R.: Charakterisierung der Mikrostruktur und Verformung in Mg-Mg-Laserschweißnähten und Al-Stahl-Reibrührschweißverbindungen. 54. Metallkunde-Kolloquium Werkstoffforschung, Lech / Österreich (2008)
Garcia, J.; Lammer, A.; Garcia, L. F.; Weber, S.; Kostka, A.; Pyzalla, A. R.: Investigations of Wear Mechanisms in Diamond Tools with Fe-Based Matrices Reinforced with WC-Co Particles. Intern. Symposium on Friction, Wear and Wear Protection, Aachen, Germany (2008)
Pyzalla, A.: Sauropoden-Dinosaurier: Giganten aus nanokristallinem Material. 29. Adelbodener Werkstoffseminar des IWK 1 der Universität Karlsruhe, Adelboden, Schweiz (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.
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.
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…