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 deals with the phase quantification by nanoindentation and electron back scattered diffraction (EBSD), as well as a detailed analysis of the micromechanical compression behaviour, to understand deformation processes within an industrial produced complex bainitic microstructure.
Within this project, we will use a green laser beam source based selective melting to fabricate full dense copper architectures. The focus will be on identifying the process parameter-microstructure-mechanical property relationships in 3-dimensional copper lattice architectures, under both quasi-static and dynamic loading conditions.
Oxides find broad applications as catalysts or in electronic components, however are generally brittle materials where dislocations are difficult to activate in the covalent rigid lattice. Here, the link between plasticity and fracture is critical for wide-scale application of functional oxide materials.
The fracture toughness of AuXSnY intermetallic compounds is measured as it is crucial for the reliability of electronic chips in industrial applications.