Predicting failure in disordered solids from structural metrics

Under applied shear, amorphous solids flow via a succession of plastic rearrangements of localized particles. Numerous numerical and experimental studies have shown that plastic instabilities in glasses are triggered by spatially localized soft spots in direct analogy with dislocations present in crystalline solids, although the population and microscopic structure of the former are significantly different from the latter. In addition, many research groups have developed methods for identifying such defects, although these methods have not been systematically compared. Here we use a swap Monte Carlo algorithm to prepare equilibrium amorphous configurations with very different stabilities that exhibit a range of behaviors under shear, from ductile flow to brittle failure. We compute various structural indicators ranging from purely structural to highly non-linear metrics that require the knowledge of the interactions between constituents. We compare these metrics on the same data sets, quantifying how well these metrics perform in predicting plastic deformation across this range of glass stabilities. Moreover, we use these structural metrics to quantify the spatial distribution of plastic defects for different preparation protocols, as well as the evolution of these defects across the yielding transition, allowing us to precisely characterize how the microscopic structure encodes the differences between ductile and brittle materials.