Counts, W. A.; Friák, M.; Raabe, D.; Neugebauer, J.: Ab Initio Guided Design of bcc Ternary Mg–Li–X (X=Ca,Al,Si,Zn,Cu) Alloys for Ultra-Lightweight Applications. Advanced Engineering Materials 12 (7), pp. 572 - 576 (2010)
Lange, B.; Freysoldt, C.; Neugebauer, J.: Native and hydrogen-containing point defects in Mg3N2: A density functional theory study. Physical Review B 81, 224109, pp. 1 - 10 (2010)
Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Rescaled Monte Carlo approach for magnetic systems: Ab initio thermodynamics of bcc iron. Physical Review B 81 (13), pp. 134425 - 134434 (2010)
von Pezold, J.; Dick, A.; Friák, M.; Neugebauer, J.: Generation and performance of special quasirandom structures for studying the elastic properties of random alloys: Application to Al–Ti. Physical Review B 81 (9), pp. 094203-1 - 094203-7 (2010)
Dick, A.; Hickel, T.; Neugebauer, J.: The Effect of Disorder on the Concentration-Dependence of Stacking Fault Energies in Fe1-xMnx – A First Principles Study. Steel Research International 80 (9), pp. 603 - 608 (2009)
Udyansky, A.; von Pezold, J.; Bugaev, N. V.; Friák, M.; Neugebauer, J.: Interplay between long-range elastic and short-range chemical interactions in Fe–C martensite formation. Physical Review B 79 (22), pp. 224112-1 - 224112-5 (2009)
Lymperakis, L.; Neugebauer, J.: Large anisotropic adatom kinetics on nonpolar GaN surfaces: Consequences for surface morphologies and nanowire growth. Physical Review B 79, pp. 241308-1 - 241308-4 (2009)
Freysoldt, C.; Boeck, S.; Neugebauer, J.: Direct minimization technique for metals in density-functional theory. Physical Review B 79, 241103(R), pp. 1 - 4 (2009)
Körmann, F.; Dick, A.; Hickel, T.; Neugebauer, J.: Pressure dependence of the Curie temperature in bcc iron studied by ab initio simulations. Physical Review B 79, 184406, pp. 184406-1 - 184406-5 (2009)
Abu-Farsakh, H.; Neugebauer, J.: Enhancing nitrogen solubility in GaAs and InAs by surface kinetics: An ab initio study. Physical Review B 79, 155311, pp. 155311 - 155323 (2009)
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 project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.