ABSTRACT
Austenitic steels with high manganese content exhibit various deformation mechanisms depending on their stacking fault energies. Here we present a novel approach of combining the algorithm of particle swarm optimization with thermodynamic modeling, to design high-manganese steels with desired stacking fault energies. Implementation of this method is demonstrated for nanostructured austenitic steels, where composition, grain size, and temperature are used as the tunable parameters. The results show that for a given value of fault energy, the proposed method yields multiple solutions, which may offer valuable guidelines for designing the alloy. In contrast with the coarse-grained steels, the design parameters of the nanostructured alloys are shown to depend on the austenitic grain size.