Realization of high-performance optical metasurfaces over a large area: a review from a design perspective

Remarkable advancements have been made in the design of optical metasurfaces in recent years, particularly in compact designs. However, for their practical integration into diverse optical systems, there is a pressing need for metasurfaces to transition toward larger areas without compromising their performance. From a design perspective, efforts in the design process must focus on reducing computational costs and enhancing performance in larger areas. In this review, we introduce diverse optical analyses applicable to wide areas, including the modification of boundary conditions, fast multipole methods, coupled mode theory, and neural network–based approaches. In addition, inverse design methods based on the adjoint method or deep learning, which are suitable for large-scale designs, are described. Numerous fast and accurate simulation methods make it possible to assess optical properties over large areas at a low cost, whereas diverse inverse design methods hold promise for high performance. By concurrently addressing both the essential aspects of designing large-area metasurfaces, we comprehensively discuss various approaches to develop metasurfaces with high performance over expansive regions. Finally, we outline additional challenges and prospects for realizing mass-produced high-performance metasurfaces, unlocking their full potential for optical applications.