Khorashadizadeh, A.; Raabe, D.; Winning, M.; Pippan, R.: Recrystallization and Grain Growth in Ultrafine-Grained Materials Produced by High Pressure Torsion. Advanced Engineering Materials 13, pp. 245 - 250 (2011)
Khorashadizadeh, A.; Raabe, D.; Zaefferer, S.; Rohrer, G. S.; Rollett, A. D.; Winning, M.: Five-Parameter Grain Boundary Analysis by 3D EBSD of an Ultra Fine Grained CuZr Alloy Processed by Equal Channel Angular Pressing. Advanced Engineering Materials 13, pp. 237 - 244 (2011)
Khorashadizadeh, A.; Winning, M.; Raabe, D.: 3D tomographic EBSD measurements of heavily deformed ultra fine grained Cu-0.17wt%Zr obtained from ECAP. Materials Science Forum 584-586, pp. 434 - 439 (2008)
Molodova, X.; Khorashadizadeh, A.; Gottstein, G.; Winning, M.; Hellmig, R. J.: Thermal Stability of ECAP Processed Pure Cu and CuZr. Inter. Journal of Materials Research 98, pp. 269 - 275 (2007)
Ram, F.; Khorashadizadeh, A.; Zaefferer, S.: Kikuchi Band Sharpness: A Measure for the Density of the Crystal Lattice Defects. MSE 2014, Darmstadt, Germany (2014)
Khorashadizadeh, A.; Raabe, D.: Exploring the formation of different lamination configurations within the orientation space. 8th European Solid Mechanics Conference 2012, Graz, Austria (2012)
Khorashadizadeh, A.; Raabe, D.: Exploring the formation of different lamination configurations within the orientation space. 11th GAMM-Seminar on Microstructures, Universität Duisburg-Essen, Essen, Germany (2012)
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
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.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…