Fujita, N.; Igi, S.; Diehl, M.; Roters, F.; Raabe, D.: The through-process texture analysis of plate rolling by coupling finite element and fast Fourier transform crystal plasticity analysis. Modelling and Simulation in Materials Science and Engineering 27, 085005 (2019)
Diehl, M.; Kertsch, L.; Traka, K.; Helm, D.; Raabe, D.: Site-specific quasi in situ investigation of primary static recrystallization in a low carbon steel. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 755, pp. 295 - 306 (2019)
Wang, D.; Diehl, M.; Roters, F.; Raabe, D.: On the role of the collinear dislocation interaction in deformation patterning and laminate formation in single crystal plasticity. Mechanics of Materials 125, pp. 70 - 79 (2018)
Diehl, M.: Review and outlook: mechanical, thermodynamic, and kinetic continuum modeling of metallic materials at the grain scale. MRS Communications 7 (4), pp. 735 - 746 (2017)
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)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
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…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.