Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Potential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Pei, R.: Microstructural Relationships of Strength and Ductility in a Newly Developed Mg–Al–Zn Alloy for Po-tential Automotive Applications. Dissertation, RWTH Aachen University (2020)
Kürnsteiner, P.: Precipitation Reactions During the Intrinsic Heat Treatment of Laser Additive Manufacturing. Dissertation, RWTH Aachen University (2019)
Dutta, A.: Deformation behaviour and texture memory effect of multiphase nano-laminate medium manganese steels. Dissertation, RWTH Aachen University (2019)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufac-turing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Hariharan, A.: On the interfacial defect formation mechanism during laser additive manufacturing of polycrystalline superalloys. Dissertation, Ruhr-Universität Bochum (2019)
Chang, Y.: Challenges and opportunities associated to the characterization of H/D in Ti and its alloys with atom probe tomography. Dissertation, RWTH Aachen University (2019)
Archie, F. M. F.: Microstructural influence on micro-damage initiation in ferritic-martensitic DP-steels. Dissertation, RWTH Aachen, Aachen, Germany (2018)
Archie, F. M. F.: Damage nucleation in DP-steels: experimental characterization of the contributing microstructural parameters. Dissertation, Fakultät für Georessourcen und Materialtechnik, RWTH Aachen (2018)
Choi, W. S.: Deformation mechanisms and the role of interfaces in face-centered cubic Fe-Mn-C micro-pillars. Dissertation, RWTH Aachen, Aachen, Germany (2018)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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.