Zhu, L.-F.; Neugebauer, J.; Grabowski, B.: A computationally highly efficient ab initio approach for melting property calculations and practical applications. CALPHAD 2024, Mannheim, Germany (2024)
Zhu, L.-F.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential and pyiron workflow. New Horizons in materials design at MPIE, Düsseldorf, Germany (2023)
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 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.
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.