An, D.; Griffiths, T. A.; Konijnenberg, P. J.; Mandal, S.; Wang, Z.; Zaefferer, S.: Correlating the five parameter grain boundary character distribution and the intergranular corrosion behaviour of a stainless steel using 3D orientation microscopy based on mechanical polishing serial sectioning. Acta Materialia 156, pp. 297 - 309 (2018)
Wang, Z.; Zaefferer, S.: On the accuracy of grain boundary character determination by pseudo-3D EBSD. Materials Characterization 130, pp. 33 - 38 (2017)
Zaefferer, S.; An, D.; Wang, Z.: Experimental investigations on the relationship between crystallographic character of grain boundaries and their functional and mechanical properties in various engineering materials. DPG Frühjahrtagung, Dresden, Germany (2017)
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)
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
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…