Characteristic Structural Motifs in Metallic Liquids and Their Relationship to Glass Forming Ability

Despite intense interest in and research on metallic glasses, one question remains predominantly unanswered: Why are certain alloys better glass-formers than others? Here, we use geometric alignment and density-based clustering algorithms to quantitatively describe the atomic structure and the degree of order in the simulated liquid state for four binary alloy systems. We show that each liquid is comprised of a surprisingly small number of characteristic atomic clusters (6-8 motifs in the systems studied), and that measurable order in metallic alloys extends far into the liquid state. The data suggests the extent of order is inversely correlated to the experimentally-observed glass-forming ability (GFA). The broad applicability of this technique to both good glass-forming systems (Cu-Zr, Ni-Nb) and poor glass-forming systems (Al-Sm, Au-Si) suggests that order in the liquid could be used as a coarse identifier of high-GFA compositions within an alloy system. This method both improves our fundamental understanding of why certain alloys are better glass-formers than others and provides an interesting a priori method for identification of potential glass-forming alloys.