Bowden, D. J.: Assessment of Co-free hardfacing stainless steel alloys for nuclear applications. Dissertation, University Manchester, Manchester, UK (2017)
Wu , X.: Elementary deformation processes during low temperature and high stress creep of Ni-base single crystal superalloys. Dissertation, Ruhr-University Bochum, Bochum, Germany (2016)
Lai, M.: Experimental-theoretical study of the interplay between deformation mechanisms and secondary phases in metastable β titanium alloys. Dissertation, RWTH Aachen, Aachen, Germany (2016)
Neddermann, P.: Martensitic Stainless Steel: Evolution of Austenite during Low Temperature Annealing and Design of Press Hardening Alloys. Dissertation, RWTH Aachen, Aachen, Germany (2016)
Zhang, J.: Microstructure design via site-specific control of recrystallization and nano-precipitation. Dissertation, RWTH Aachen, Aachen, Germany (2016)
Szczepaniak, A.: Investigation of intermetallic layer formation in dependence of process parameters during the thermal joining of aluminium with steel. Dissertation, RWTH Aachen, Aachen, Germany (2016)
Nellessen, J.: Effects of strain amplitude, cycle number and orientation on low cycle fatigue microstructures in austenitic stainless steel and aluminum. Dissertation, RWTH Aachen, Aachen, Germany (2015)
Diehl, M.: High Resolution Crystal Plasticity Simulations. Dissertation, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen, Germany (2015)
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
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…
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.