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)
If manganese nodules can be mined in an environmentally friendly way, the critical metals needed for the energy transition could be produced with low CO2 emissions
Alper Kasirga wins the Max Planck Apprenticeship Award and the Max Planck Institute for Sustainable Materials is recognised as an excellent training institution