Diehl, M.; Groeber, M.; Haase, C.; Roters, F.; Raabe, D.: Identifying Structure–Property Relationships Through DREAM.3D Representative Volume Elements and DAMASK Crystal Plasticity Simulations: An Integrated Computational Materials Engineering Approach. JOM-Journal of the Minerals Metals & Materials Society 69 (5), pp. 848 - 855 (2017)
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)
Zhang, H.; Diehl, M.; Roters, F.: A virtual laboratory using high resolution crystal plasticity simulations to determine the initial yield surface for sheet metal forming operations. International Journal of Plasticity 80, pp. 111 - 138 (2016)
Cereceda, D.; Diehl, M.; Roters, F.; Raabe, D.; Perlado, J. M.; Marian, J.: Unraveling the temperature dependence of the yield strength in single-crystal tungsten using atomistically-informed crystal plasticity calcula- tions. International Journal of Plasticity 78, pp. 242 - 265 (2016)
Diehl, M.; Shanthraj, P.; Eisenlohr, P.; Roters, F.: Neighborhood influences on stress and strain partitioning in dual-phase microstructures. An investigation on synthetic polycrystals with a robust spectral-based numerical method. Meccanica 51 (2), pp. 429 - 441 (2016)
Tjahjanto, D. D.; Eisenlohr, P.; Roters, F.: Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme. Modelling and Simulation in Materials Science and Engineering 23 (4), 045005 (2015)
Bambach, M.; Heppner, S.; Steinmetz, D.; Roters, F.: Assessing and ensuring parameter identifiability for a physically-based strain hardening model for twinning-induced plasticity. Mechanics of Materials 84, pp. 127 - 139 (2015)
Shanthraj, P.; Eisenlohr, P.; Diehl, M.; Roters, F.: Numerically robust spectral methods for crystal plasticity simulations of heterogeneous materials. International Journal of Plasticity 66, pp. 31 - 45 (2015)
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
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…
Electron channelling contrast imaging (ECCI) is a powerful technique for observation of extended crystal lattice defects (e.g. dislocations, stacking faults) with almost transmission electron microscopy (TEM) like appearance but on bulk samples in the scanning electron microscope (SEM).
Water electrolysis has the potential to become the major technology for the production of the high amount of green hydrogen that is necessary for its widespread application in a decarbonized economy. The bottleneck of this electrochemical reaction is the anodic partial reaction, the oxygen evolution reaction (OER), which is sluggish and hence…