Zhu, L.-F.; Körmann, F.; Chen, Q.; Selleby, M.; Neugebauer, J.; Grabowski, B.: Accelerating ab initio melting property calculations with machine learning: application to the high entropy alloy TaVCrW. npj Computational Materials 10 (1), 274 (2024)
Zhu, L.-F.; Körmann, F.; Ruban, A. V.; Neugebauer, J.; Grabowski, B.: Performance of the standard exchange-correlation functionals in predicting melting properties fully from first principles: Application to Al and magnetic Ni. Physical Review B 101 (14), 144108 (2020)
Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Efficient approach to compute melting properties fully from ab initio with application to Cu. Physical Review B 96 (22), 224202 (2017)
Sandlöbes, S.; Friák, M.; Dick, A.; Zaefferer, S.; Yi, S.; Letzig, D.; Pei, Z.; Zhu, L.-F.; Neugebauer, J.; Raabe, D.: Complementary TEM and ab ignition study on the ductilizing effect of Y in solid solution Mg–Y alloys. In: Proceedings of the 9th Intern. Conference on Magnesium alloys and their applications, pp. 467 - 472. 9th Intern. Conference on Magnesium alloys and their applications, Vancouver, Canada, July 08, 2012 - July 12, 2012. (2012)
Zhu, L.-F.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential. The third generation (3G) Calphad at KTH, Stockholm, Sweden (2023)
Zhu, L.-F.; Neugebauer, J.; Grabowski, B.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential. CALPHAD L Conference, Cambridge, MA, USA (2023)
Zhu, L.-F.: Melting properties from ab initio using efficient TOR-TILD approach: Applications to refractory metals V, W and V–W alloy. CALPHAD XLVIII Conference, Stockholm, Sweden (2023)
Zhu, L.-F.: Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential and pyiron workflow. CM retreat, Ebernburg, Germany (2022)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
The aim of the Additive micromanufacturing (AMMicro) project is to fabricate advanced multimaterial/multiphase MEMS devices with superior impact-resistance and self-damage sensing mechanisms.
TiAl-based alloys currently mature into application. Sufficient strength at high temperatures and ductility at ambient temperatures are crucial issues for these novel light-weight materials. By generation of two-phase lamellar TiAl + Ti3Al microstructures, these issues can be successfully solved. Because oxidation resistance at high temperatures is…
We will investigate the electrothermomechanical response of individual metallic nanowires as a function of microstructural interfaces from the growth processes. This will be accomplished using in situ SEM 4-point probe-based electrical resistivity measurements and 2-point probe-based impedance measurements, as a function of mechanical strain and…
Laser Powder Bed Fusion (LPBF) is the most commonly used Additive Manufacturing processes. One of its biggest advantages it offers is to exploit its inherent specific process characteristics, namely the decoupling the solidification rate from the parts´volume, for novel materials with superior physical and mechanical properties. One prominet…