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)
Water electrolysis has the potential to become the major technology for the production of the high amount of green hydrogen that is necessary for its widespread application in a decarbonized economy. The bottleneck of this electrochemical reaction is the anodic partial reaction, the oxygen evolution reaction (OER), which is sluggish and hence…
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.
The group aims at unraveling the inner workings of ion batteries, with a focus on probing the microstructural and interfacial character of electrodes and electrolytes that control ionic transport and insertion into the electrode.
The full potential of energy materials can only be exploited if the interplay between mechanics and chemistry at the interfaces is well known. This leads to more sustainable and efficient energy solutions.
In order to develop more efficient catalysts for energy conversion, the relationship between the surface composition of MXene-based electrode materials and its behavior has to be understood in operando. Our group will demonstrate how APT combined with scanning photoemission electron microscopy can advance the understanding of complex relationships…
To advance the understanding of how degradation proceeds, we use the latest developments in cryo-atom probe tomography, supported by transmission-electron microscopy. The results showcase how advances in microscopy & microanalysis help bring novel insights into the ever-evolving microstructures of active materials to support the design of better…