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)
Neugebauer, J.; Huber, L.; Körmann, F.; Grabowski, B.; Hickel, T.: Ab initio input for multiphysics models: Accuracy, performance and challenges. ISAM4: The fourth International Symposium on Atomistic and Multiscale Modeling of Mechanics and Multiphysics, Erlangen, Germany (2019)
Zhu, L.-F.; Janßen, J.; Grabowski, B.; Neugebauer, J.: Melting parameters from ab initio using the fast statistical sampling TOR-TILD approach: Applications to Al and Ni. CALPHAD XLVIII CONFERENCE, Singapore, Singapore (2019)
Neugebauer, J.; Todorova, M.; Grabowski, B.; Hickel, T.: Modelling structural materials in realistic environments by ab initio thermodynamics. Hume-Rothery Award Symposium, TMS2019 Annual Meeting and Exhibition, San Antonio, TX, USA (2019)
Neugebauer, J.; Janßen, J.; Körmann, F.; Hickel, T.; Grabowski, B.: Exploration of large ab initio data spaces to design materials with superior mechanical properties. Physics and Theoretical Division Colloquium, Los Alamos, NM, USA (2019)
Zhu, L.-F.; Grabowski, B.; Neugebauer, J.: Efficient approach to compute melting properties fully from ab initio with application to Cu. CALPHAD XLVII Conference, Querétaro, México (2018)
Grabowski, B.: Knowledge driven engineering of materials: Development and application of ab initio based scale bridging methods. Seminar at HSU Hamburg, Hamburg, Germany (2018)
Grabowski, B.: Efficient and Accurate Computation of Melting Temperatures and Enthalpies and Entropies of Fusion from Ab Initio. TMS conference, Phoenix, AZ, USA (2018)
Grabowski, B.: Knowledge driven engineering of materials: Development and application of ab initio based scale bridging methods. Seminar at University Stuttgart, Stuttgart, Germany (2017)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
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…
This project studies the mechanical properties and microstructural evolution of a transformation-induced plasticity (TRIP)-assisted interstitial high-entropy alloy (iHEA) with a nominal composition of Fe49.5Mn30Co10Cr10C0.5 (at. %) at cryogenic temperature (77 K). We aim to understand the hardening behavior of the iHEA at 77 K, and hence guide the future design of advanced HEA for cryogenic applications.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization as in micropillar compression. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one.…
Because of their excellent corrosion resistance, high wear resistance and comparable low density, Fe–Al-based alloys are an interesting alternative for replacing stainless steels and possibly even Ni-base superalloys. Recent progress in increasing strength at high temperatures has evoked interest by industries to evaluate possibilities to employ…