Wan, D.; Ma, Y.; Sun, B.; Razavi, S. M. J.; Wang, D.; Lu, X.; Song, W.: Evaluation of hydrogen effect on the fatigue crack growth behavior of medium-Mn steels via in-situ hydrogen plasma charging in an environmental scanning electron microscope. Journal of Materials Science & Technology 85, pp. 30 - 43 (2021)
Sun, B.; Ma, Y.; Vanderesse, N.; Srinivas Varanasi, R.; Song, W.; Bocher, P.; Ponge, D.; Raabe, D.: Macroscopic to nanoscopic in situ investigation on yielding mechanisms in ultrafine grained medium Mn steels: Role of the austenite-ferrite interface. Acta Materialia 178, pp. 10 - 25 (2019)
Song, W.: Characterization and simulation of bainite transformation in high carbon bearing steel 100Cr6. Dissertation, RWTH Aachen, Aachen, Germany (2014)
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
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…