Cedat, D.: Modeling and Experiment on Mo-based high temperature composites. Dissertation, Ecole Centrale Paris, Laboratoire for Materials, Paris [France] (2008)
Sachs, C.: Microstructure and mechanical properties of the exoskeleton of the lobster Homarus americanus as an example of a biological composite material. Dissertation, RWTH Aachen, Aachen, Germany (2008)
Tjahjanto, D.: Micromechanical Modeling and Simulations of Tranformation-Induced Plasticity in Multiphase Carbon Steels. Dissertation, TU Delft, Delft, The Netherlands (2008)
Klüber, C.: Korrelation von mechanischen Eigenschaften und Kristallorientierung auf mikroskopischer und nanoskopischer Ebene. Dissertation, RWTH Aachen, Aachen, Germany (2008)
Bastos da Silva, A. F.: Characterization of the Microstructure, Grain Boundaries and Texture of Nanostructured Electrodeposited CoNi by use of EBSD. Dissertation, RWTH Aachen, Aachen, Germany (2007)
Goerdeler, M.: Application of a dislocation density based flow stress model in the integrative through-process modeling of Aluminium production. Dissertation, RWTH Aachen, Aachen, Germany (2007)
Wolff, C.: Der tribologisch asymmetrische Flachstauchversuch - Eine neue Methode zur Analyse von Reibungsvorgängen bei Umformprozessen. Dissertation, RWTH Aachen, Aachen, Germany (2001)
Kaushal, C.: Untersuchung der Abhängigkeit des Ölaustrags von der Oberflächenfeinstruktur beim Auswalzen gedoppelter Aluminiumfolien. Diploma, HS Niederrhein, Krefeld, Germany (2003)
Tranchant, J.: Deformation of Semi-Brittle Intermetallic Material under Superimposed Hydrostatic Pressure. Diploma, Ecole Centrale de Nantes, Nantes, France (2002)
Paiva do Nascimento, A. W.: An optimized method to determine initial parameters of advanced yield surfaces for sheet metal form-ing applications. Master, Ruhr-Universität Bochum (2021)
Kusampudi, N.: Using Machine Learning and Data-driven Approaches to Predict Damage Initiation in Dual-Phase Steels. Master, Ruhr-Universität Bochum (2020)
Soundararajan, C. K.: Recrystallization behavior and mechanical properties of interstitially alloyed CoCrFeMnNi equiatomic high entropy alloy. Master, RWTH Aachen University (2020)
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…
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
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…