Diehl, M.; Wicke, M.; Shanthraj, P.; Roters, F.; Brueckner-Foit, A.; Raabe, D.: Coupled Crystal Plasticity–Phase Field Fracture Simulation Study on Damage Evolution Around a Void: Pore Shape Versus Crystallographic Orientation. JOM-Journal of the Minerals Metals & Materials Society 69 (5), pp. 872 - 878 (2017)
Koprek, A.; Cojocaru-Mirédin, O.; Würz, R.; Freysoldt, C.; Gault, B.; Raabe, D.: Cd and Impurity Redistribution at the CdS/CIGS Interface After Annealing of CIGS-Based Solar Cells Resolved by Atom Probe Tomography. IEEE Journal of Photovoltaics 7 (1), 7762819, pp. 313 - 321 (2017)
Li, Y.; Herbig, M.; Goto, S.; Raabe, D.: Atomic scale characterization of white etching area and its adjacent matrix in a martensitic 100Cr6 bearing steel. Materials Characterization 123, pp. 349 - 353 (2017)
Lübke, A.; Loza, K.; Patnaik, R.; Enax, J.; Raabe, D.; Prymak, O.; Fabritius, H.-O.; Gaengler, P.; Epple, M.: Reply to the ‘Comments on “Dental lessons from past to present: ultrastructure and composition of teeth from plesiosaurs, dinosaurs, extinct and recent sharks”’ by H. Botella et al., RSC Adv., 2016, 6, 74384–74388. RSC Advances 7 (11), pp. 6215 - 6222 (2017)
Baron, C.; Springer, H.; Raabe, D.: Combinatorial screening of the microstructure–property relationships for Fe–B–X stiff, light, strong and ductile steels. Materials and Design 112, pp. 131 - 139 (2016)
Baron, C.; Springer, H.; Raabe, D.: Effects of Mn additions on microstructure and properties of Fe–TiB2 based high modulus steels. Materials and Design 111, pp. 185 - 191 (2016)
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…