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)
Otto de Mentock, D.; Roongta, S.; Shanthraj, P.; Eisenlohr, P.; Diehl, M.; Roters, F.: Challenges of Developing and Scaling up DAMASK, a Unified Large-strain Multi-physics Crystal Plasticity Simulation Software. TMS - Algorithm Development in Materials Science and Engineering, Orlando, FL, USA (2024)
Roters, F.; do Nascimento, A. W. P.; Roongta, S.; Diehl, M.: An optimized method for the simulation-based determination of initial parameters of advanced yield surfaces for sheet metal forming applications. Complas 2021, online (2021)
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
This project aims to investigate the dynamic hardness of B2-iron aluminides at high strain rates using an in situ nanomechanical tester capable of indentation up to constant strain rates of up to 100000 s−1 and study the microstructure evolution across strain rate range.