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)
Zhou, Y.; Srinivasan, P.; Körmann, F.; Grabowski, B.; Smith, R.; Goddard, P.; Duff, A. I.: Thermodynamics up to the melting point in a TaVCrW high entropy alloy: Systematic ab initio study aided by machine learning potentials. Physical Review B 105 (21), 214302 (2022)
Dsouza, R.; Huber, L.; Grabowski, B.; Neugebauer, J.: Approximating the impact of nuclear quantum effects on thermodynamic properties of crystalline solids by temperature remapping. Physical Review B 105 (18), 184111 (2022)
Novikov, I.; Grabowski, B.; Körmann, F.; Shapeev, A.: Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe. npj Computational Materials 8 (1), 13 (2022)
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)
Max Planck team explains dendrite propagation, paving the way for safer and longer-lasting next-generation batteries. They publish their findings in the journal Nature.
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
In this project, we aim to design novel NiCoCr-based medium entropy alloys (MEAs) and further enhance their mechanical properties by tuning the multiscale heterogeneous composite structures. This is being achieved by alloying of varying elements in the NiCoCr matrix and appropriate thermal-mechanical processing.