Brinckmann, S.: Using Simulations to Investigate the Apparent Fracture Toughness of Microcantilevers. STKS-ICAMS-Seminar, RUB Bochum, Bochum, Germany (2018)
Brinckmann, S.: Understanding the fracture toughness for brittle and ductile materials at the microscale. Materials Science and Engineering-MSE 2018, Darmstadt, Germany (2018)
Duarte, M. J.; Fang, X.; Brinckmann, S.; Dehm, G.: New approaches for in-situ nanoindentation of hydrogen charged alloys: insights on bcc FeCr alloys. DPG Spring Meeting of the Condensed Matter Section, Berlin, Germany (2018)
Brinckmann, S.: Microscale Materials Tribology: Severe Deformation of Pearlite. Talk at Institut für Konstruktionswissenschaften und Technische Logistik, Technische Universität Wien, Wien, Austria (2017)
Brinckmann, S.: Severe Deformation of Pearlite during Microscale Tribology. Talk at Erich Schmid Institute für Materialwissenschaft, Leoben, Austria (2017)
Brinckmann, S.; Kirchlechner, C.; Dehm, G.; Matoy, K.: Using simulations to investigate the apparent fracture toughness of microcantilevers. Nanomechanical Testing in Materials Research and Development VI, Dubrovnik, Croatia (2017)
Duarte, M. J.; Fang, X.; Brinckmann, S.; Dehm, G.: In-situ nanoindentation of hydrogen bcc Fe–Cr charged surfaces: Current status and future perspectives. Frontiters in Material Science & Engineering workshop: Hydrogen Interaction in Metals, Max-Planck Institut für Eisenforschung, Düsseldorf, Germany (2017)
Brinckmann, S.; Fink, C.; Dehm, G.: Severe Microscale Deformation of Pearlite and Cementite. 2017 MRS Spring Meeting & Exhibits, Phoenix, AZ, USA (2017)
Scientists at the Max Planck Institute for Sustainable Materials have developed a carbon-free, energy-saving method to extract nickel for batteries, magnets and stainless steel.
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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