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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.