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)
Hamidi Siboni, N.: Molecular Dynamics Studies of Thermodynamical Consistency and Non-locality of Effective Temperature. Dissertation, Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen, Germany (2014)
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)
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…