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)
Wang, Z.: Investigation of crystallographic character and molten-salt-corrosion properties of grain boundaries in a stainless steel using EBSD and ab-initio calculations. Dissertation, Ruhr-Universität Bochum, Bochum, Germany (2017)
Elhami, N. N.: Influence of strain path changes during cup drawing on the twinning activity in TWIP steels investigated by ECCI. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Stechmann, G.: A Study on the Microstructure Formation Mechanisms and Functional Properties of CdTe Thin Film Solar Cells Using Correlative Electron Microscopy and Atomistic Simulations. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Ram, F.: The Kikuchi bandlet method for the intensity analysis of the Electron Backscatter Kikuchi Diffraction Patterns. Dissertation, RWTH Aachen, Aachen, Germany (2015)
Schemmann, L.: The inheritance of different microstructures found after hot rolling on the properties of a completely annealed dual phase steel. Dissertation, Fakultät für Georessourcen und Materialtechnik, RWTH Aachen, Aachen, Germany (2014)
Jäpel, T.: Feasibility study on local elastic strain measurements with an EBSD pattern cross correlation method in elastic-plastically deforming material. Dissertation, RWTH Aachen, Aachen, Germany (2014)
Elhami, N.-N.: Schädigungsmechanismen und Entwicklung der Mikrostruktur eines Al-legierten TRIP-Stahls im Laufe der Verformung. Diploma, RWTH Aachen, Aachen, Germany (2008)
Shan, Y.: Investigation on the Influence of Hydrogen on Dislocation Formation during Nanoindentation in TWIP Steels. Master, RWTH Aachen, Aachen, Germany (2018)
Kuo, J. C.; Zaefferer, S.; Raabe, D.: Experimental investigation of the deformation behavior of aluminium-bicrystals. MPI für Eisenforschung GmbH, Düsseldorf, Germany (2004)
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.
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…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.