(Peer-Reviewed) High-efficiency infrared upconversion imaging with nonlinear silicon metasurfaces empowered by quasi-bound states in the continuum
Tingting Liu 刘婷婷 ¹ ², Jumin Qiu 邱驹敏 ³, Meibao Qin 秦梅宝 ³ ⁴, Xu Tu 涂旭 ², Huifu Qiu 邱辉福 ², Feng Wu 吴丰 ⁵, Tianbao Yu 于天宝 ³, Qiegen Liu 刘且根 ¹, Shuyuan Xiao 肖书源 ¹ ²
¹ School of Information Engineering, Nanchang University, Nanchang 330031, China
中国 南昌 南昌大学信息工程学院
² Institute for Advanced Study, Nanchang University, Nanchang 330031, China
中国 南昌 南昌大学高等研究院
³ School of Physics and Materials Science, Nanchang University, Nanchang 330031, China
中国 南昌 南昌大学物理与材料学院
⁴ School of Education, Nanchang Institute of Science and Technology, Nanchang 330108, China
中国 南昌 南昌工学院教育学院
⁵ School of Optoelectronic Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China
中国 广州 广东技术师范大学光电工程学院
Opto-Electronic Advances, 2026-01-29
Abstract
Infrared imaging is indispensable for its ability to penetrate obscurants and visualize thermal signatures, yet its practical use is hindered by the intrinsic limitations of conventional detectors. Nonlinear upconversion, which converts infrared light into the visible band, offers a promising pathway to address these challenges. Here, we demonstrate high-efficiency infrared upconversion imaging using nonlinear silicon metasurfaces.
By strategically breaking in-plane symmetry, the metasurface supports a high-Q quasi-bound states in the continuum resonance, leading to strongly enhanced third-harmonic generation (THG) with a conversion efficiency of 3×10−5 at a pump intensity of 10 GW/cm2. Through this THG process, the metasurface enables high-fidelity upconversion of arbitrary infrared images into the visible range, achieving a spatial resolution of ~6 μm as verified using a resolution target and various customized patterns.
This work establishes a robust platform for efficient nonlinear conversion and imaging, highlighting the potential of CMOS-compatible silicon metasurfaces for high-performance infrared sensing applications with reduced system complexity.
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