AI-based optical materials discovery

The field of metamaterials allows for the creation of materials with extraordinary properties. However, the development of materials with specific, custom properties is regarded as a challenging task. Current materials-by- design methodologies hinge on a trial-and-error approach, employing serendipitous techniques that prove inefficient and impractical. Furthermore, the extensive variety of materials and the myriad ways they can be combined in different ratios contribute to an infinite compositional space. Here, we present a universal machine-learning method that identifies the complex, nonlinear relationship between an amorphous metamaterial's structural characteristics and on-demand optical properties, all within a matter of milliseconds. As a proof of concept, we have demonstrated two practical applications of the method experimentally by developing a custom metasurface-perfect reflector. This innovative approach empowers users to craft materials of interest without depending on intuitions, prior experiences, or extensive simulation and modelling, potentially paving the way for the accelerated discovery of new materials.