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
Biological materials in nature have a lot to teach us when in comes to creating tough bio-inspired designs. This project aims to explore the unknown impact mitigation mechanisms of the muskox head (ovibus moschatus) at several length scales and use this gained knowledge to develop a novel mesoscale (10 µm to 1000 µm) metamaterial that can mimic the…
Grain boundaries are one of the most important constituents of a polycrystalline material and play a crucial role in dictating the properties of a bulk material in service or under processing conditions. Bulk properties of a material like fatigue strength, corrosion, liquid metal embrittlement, and others strongly depend on grain boundary…
Hydrogen embrittlement remains a strong obstacle to the durability of high-strength structural materials, compromising their performance and longevity in critical engineering applications. Of particular relevance is the effect of mobile and trapped hydrogen at interfaces, such as grain and phase boundaries, since they often determine the material’s…
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.