Designing for Cooperative Grain Boundary Segregation in Multicomponent Alloys

Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only competition is possible between solute species. In this paper, we show that solute elements can cooperate in the way they segregate to grain boundaries: in properly targeted alloys, the different chemical species cooperate to each fill complementary grain boundary sites disfavored by the other. By developing a theoretical "spectral" approach to this problem based on quantum-accurate grain boundary site distributions, we show how grain boundaries can be cooperatively alloyed, whether by depletion or enrichment. We provide machine-learned co-segregation information for over 700 ternary aluminum-based alloys, and experimentally validate the concept in one ternary alloy where co-segregation is not expected by prior models, but is expected based on the cooperative model.