Characterizing the mechanical response of metallic glasses using spring network models

Bulk metallic glasses (BMG) are amorphous alloys with many desirable properties such as high yield strength and elasticity. Due to their disordered structure and complex response to applied stress, it is difficult to predict whether a given BMG sample will deform in a ductile or brittle manner. Using molecular dynamics simulations, we generated binary Lennard-Jones (LJ) glasses over a range of cooling rates. We then performed athermal quasistatic tension tests on these samples to obtain a wide range of force versus strain responses. To analyze and interpret this data, we developed a spring network model, where springs can break and reform based on atomic rearrangements. We calibrate the spring network model using the probability distribution that a spring of given length and angle relative to the pulling direction will break by measuring changes in the Voronoi neighbors as a function of strain in the LJ simulations. We find that the force versus strain curves from the spring model agree quantitatively with those from the LJ simulations. The spring network model gives insight into the important parameters that control the mechanical response of BMGs.