Patil, P.; Lee, S.; Dehm, G.; Brinckmann, S.: Influence of crystal orientation on twinning in austenitic stainless-steel during single micro-asperity tribology and nanoindentation. WEAR 504-505, 204403 (2022)
Tsybenko, H.; Farzam, F.; Dehm, G.; Brinckmann, S.: Scratch hardness at a small scale: Experimental methods and correlation to nanoindentation hardness. Tribology International 163, 107168 (2021)
Duarte, M. J.; Fang, X.; Rao, J.; Krieger, W.; Brinckmann, S.; Dehm, G.: In situ nanoindentation during electrochemical hydrogen charging: a comparison between front-side and a novel back-side charging approach. Journal of Materials Science 56 (14), pp. 8732 - 8744 (2021)
Ebner, A. S.; Brinckmann, S.; Plesiutschnig, E.; Clemens, H.; Pippan, R.; Maier-Kiener, V.: A Modified Electrochemical Nanoindentation Setup for Probing Hydrogen-Material Interaction Demonstrated on a Nickel-Based Alloy. JOM-Journal of the Minerals Metals & Materials Society 72 (5), pp. 2020 - 2029 (2020)
Brinckmann, S.: A framework for material calibration and deformation predictions applied to additive manufacturing of metals. International Journal of Fracture 218, pp. 85 - 95 (2019)
Brinckmann, S.: The third Sandia fracture challenge: predictions of ductile fracture in additively manufactured metal. International Journal of Fracture 218 (1-2), pp. 5 - 61 (2019)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.