Structuro-elasto-plasticity model for large deformation of disordered solids

Elastoplastic lattice models for the response of solids to large-scale deformation typically incorporate structure only implicitly via a local yield strain that is assigned each site. However, can change in nearby or even distant plastic event system. This interplay key understanding phenomena such as avalanches which one trigger another, leading cascade events, but neglected elastoplastic models. To include could calculate given particulate system and follow its evolution, this expensive requires knowledge particle interactions aren't necessarily pairwise additive possible extract from experiments. Instead, we use structural quantity, ``softness,'' obtained using machine learning correlate with imminent rearrangements. We show softness correlates it construct ``structuro-elasto-plasticity'' model reproduces simulation results reasonably well several observable quantities, confirming capture influence structure, plasticity, elasticity on material response.