Kusampudi, N.; Diehl, M.: Inverse design of dual-phase steel microstructures using generative machine learning model and Bayesian optimization. International Journal of Plasticity 171, 103776 (2023)
Nascimento, A.; Roongta, S.; Diehl, M.; Beyerlein, I. J.: A machine learning model to predict yield surfaces from crystal plasticity simulations. International Journal of Plasticity 161, 103507 (2023)
Shah, V.; Sedighiani, K.; Van Dokkum, J. S.; Bos, C.; Roters, F.; Diehl, M.: Coupling crystal plasticity and cellular automaton models to study meta- dynamic recrystallization during hot rolling at high strain rates. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 849, 143471 (2022)
Fujita, N.; Yasuda, K.; Ishikawa, N.; Diehl, M.; Roters, F.; Raabe, D.: Characterizing Localized Microstructural Deformation of Multiphase Steel by Crystal Plasticity Simulation with Multi-Constitutive Law. Journal of the Japan Society for Technology of Plasticity 63 (732), pp. 1 - 8 (2022)
Sedighiani, K.; Diehl, M.; Traka, K.; Roters, F.; Sietsma, J.; Raabe, D.: An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curves. International Journal of Plasticity 134, 102779 (2020)
Han, F.; Diehl, M.; Roters, F.; Raabe, D.: Using spectral-based representative volume element crystal plasticity simulations to predict yield surface evolution during large scale forming simulations. Journal of Materials Processing Technology 277, 116449 (2020)
Diehl, M.; Niehuesbernd, J.; Bruder, E.: Quantifying the Contribution of Crystallographic Texture and Grain Morphology on the Elastic and Plastic Anisotropy of bcc Steel. Metals 9 (12), 1252 (2019)
Diehl, M.; Kühbach, M.: Coupled experimental-computational analysis of primary static recrystallization in low carbon steel. Modelling and Simulation in Materials Science and Engineering 28 (1), 014001 (2019)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
The aim of the work is to develop instrumentation, methodology and protocols to extract the dynamic strength and hardness of micro-/nano- scale materials at high strain rates using an in situ nanomechanical tester capable of indentation up to constant strain rates of up to 100000 s−1.
In this project, we investigate a high angle grain boundary in elemental copper on the atomic scale which shows an alternating pattern of two different grain boundary phases. This work provides unprecedented views into the intrinsic mechanisms of GB phase transitions in simple elemental metals and opens entirely novel possibilities to kinetically engineer interfacial properties.
Within this project, we will use an infra-red laser beam source based selective powder melting to fabricate copper alloy (CuCrZr) architectures. The focus will be on identifying the process parameter-microstructure-mechanical property relationships in 3-dimensional CuCrZr alloy lattice architectures, under both quasi-static and dynamic loading…
Copper is widely used in micro- and nanoelectronics devices as interconnects and conductive layers due to good electric and mechanical properties. But especially the mechanical properties degrade significantly at elevated temperatures during operating conditions due to segregation of contamination elements to the grain boundaries where they cause…