Learning the dynamics of metamaterials from diffracted waves with convolutional neural networks

Abstract

Scattered elastic waves provide non-invasive diagnostics and dynamic characterization of metamaterials, but extracting information from small-size samples is challenging. Here, convolutional neural networks are used to interpret diffracted waves, revealing how sample-edge scattering provides the most significant information on macroscopic metamaterial properties.