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)
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…
The aim of the current study is to investigate electrochemical corrosion mechanisms by examining the metal-liquid nanointerfaces. To achieve this, corrosive fluids will be strategically trapped within metal structures using novel additive micro fabrication techniques. Subsequently, the nanointerfaces will be analyzed using cryo-atom probe…
In this project we pursue recent developments in the field of austenitic steels with up to 18% reduced mass density. The alloys are based on the Fe-Mn-Al-C system.
Local lattice distortion is one of the core effects in complex concentrated alloys (CCAs). It has been expected that the strength CCAs can be improved by inducing larger local lattice distortions. In collaboration with experimentalists, we demonstrated that VCoNi has larger local lattice distortions and indeed has much better strength than the…
Electro-responsive interfaces alter their properties in response to an electric potential trigger. Hence, such 'smart' interfaces offer exciting possibilities for applications in, for instance, microfluidics, separation systems, biosensors and -analytics.
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.
In this project we study a new strategy for the theory-guided bottom up design of beta-Ti alloys for biomedical applications using a quantum mechanical approach in conjunction with experiments. Parameter-free density functional theory calculations are used to provide theoretical guidance in selecting and optimizing Ti-based alloys...