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 scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
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…