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)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
This project targets to exploit or develop new methodologies to not only visualize the 3D morphology but also measure chemical distribution of as-synthesized nanostructures using atom probe tomography.