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)
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 influence of grain boundaries on mechanical behavior at ultra-high strain rates and low temperatures. For this micropillar compressions on copper bi-crystals containing different grain boundaries will be performed.
The objective of the project is to investigate grain boundary precipitation in comparison to bulk precipitation in a model Al-Zn-Mg-Cu alloy during aging.
This project aims to develop a testing methodology for the nano-scale samples inside an SEM using a high-speed nanomechanical low-load sensor (nano-Newton load resolution) and high-speed dark-field differential phase contrast imaging-based scanning transmission electron microscopy (STEM) sensor.
Understanding hydrogen-microstructure interactions in metallic alloys and composites is a key issue in the development of low-carbon-emission energy by e.g. fuel cells, or the prevention of detrimental phenomena such as hydrogen embrittlement. We develop and test infrastructure, through in-situ nanoindentation and related techniques, to study…