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)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
The structures of grain boundaries (GBs) have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the near-atomic scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability…
Hydrogen embrittlement is one of the most substantial issues as we strive for a greener future by transitioning to a hydrogen-based economy. The mechanisms behind material degradation caused by hydrogen embrittlement are poorly understood owing to the elusive nature of hydrogen. Therefore, in the project "In situ Hydrogen Platform for…
The Atom Probe Tomography group in the Microstructure Physics and Alloy Design department is developing integrated protocols for ultra-high vacuum cryogenic specimen transfer between platforms without exposure to atmospheric contamination.
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…
The computational materials design department in collaboration with the Technical University Darmstadt and the Ruhr University Bochum developed a workflow to calculate phase diagrams from ab-initio. This achievement is based on the expertise in the ab-initio thermodynamics in combination with the recent advancements in machine-learned interatomic…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.