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)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.