Work

Flexible conformal polarization-sensitive structural color optical switch

Year: 2025

Type: article

Abstract: Traditional metasurface structural color design faces limitations in computational efficiency and optical switching mechanisms. This study introduces a bidirectional deep neural network (Bi-DNN) platform for the inverse design of a flexible polarization-sensitive color switch. The trained model enables simultaneous bidirectional prediction of structural parameters and output colors, achieving prediction speeds of 64 ms per sample–three orders of magnitude faster than conventional finite-difference time-domain (FDTD) simulations. Under mechanical tuning (-10% to 50% strain), the metasurface achieves a color gamut covering 92% sRGB while maintaining target color accuracy (Δ E < 2) via Bi-DNN driving. The device enables color display or hiding through orthogonal linear polarization switching, achieving a maximum extinction ratio of 17.1 dB within the visible spectrum. Angularly stable performance preserves color fidelity over incidence angles of 0°-20°. This work establishes a new paradigm for high-performance optical switches and advances inverse-design foundations for directional color metasurfaces, with applications in next-generation displays, smart wearables, and optical encryption systems.

Source: Optics Express

DOI: 10.1364/oe.572162