Stechmann, G.; Zaefferer, S.; Raabe, D.: Molecular statics simulation of CdTe grain boundary structures and energetics using a bond-order potential. Modelling and Simulation in Materials Science and Engineering 26 (4), 045009 (2018)
Jafari, M.; Jamshidian, M.; Ziaei-Rad, S.; Raabe, D.; Roters, F.: Constitutive modeling of strain induced grain boundary migration via coupling crystal plasticity and phase-field methods. International Journal of Plasticity 99, pp. 19 - 42 (2017)
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
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.
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…