Contrast-Enhanced Nonlinear Imaging with Moiré Flatband Superlattices
Amin Zamani, Lihang Feng, Jianji Liu, Ze Zheng, Gabriel Sanderson, Mohsen Rahmani, Peilong Hong, Lei Xu
Abstract
Nonlinear metasurfaces offer a compact platform for infrared-to-visible conversion and imaging, yet resonant enhancement is often accompanied by restricted angular acceptance, limiting the range of transverse spatial frequencies that can interact efficiently with the nonlinear modes. Here, we address this challenge using a one-dimensional photonic moiré superlattice supporting multiple quasi-flat bands in the near-infrared. These moiré modes combine strong near-field enhancement with broad momentum-space accessibility, enabling efficient third-harmonic generation (THG) while maintaining stable excitation over a large angular range. Experimentally, we observe strong THG emission near 467~nm under broadband excitation from 1180 to 2000~ nm . We further employ the nonlinear moiré superlattice for infrared imaging by converting an infrared target into visible through the THG process. By encoding image information into displacement-dependent THG signals and decoding their spatial variations, we experimentally resolve weak features and internal textures with improved contrast compared with THG imaging using nonlinear films or conventional nonlinear metasurfaces. These results establish photonic moiré superlattices as a versatile platform combining efficient frequency conversion, broad angular acceptance, and mode-sensitive spatial encoding for high-contrast, label-free nonlinear imaging with enhanced feature discrimination.
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