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)
Bleskov, I.; Hickel, T.; Neugebauer, J.; Ruban, A. V.: Impact of local magnetism on stacking fault energies: A first-principles investigation for fcc iron. Physical Review B 93 (21), 214115 (2016)
Ruban, A. V.; Razumovskiy, V. I.; Körmann, F.: Erratum: Spin-wave method for the total energy of paramagnetic state (Phys. Rev. B (2012) 85 (174407)). Physical Review B 89 (17), 179901 (2014)
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 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.