Design of a polarization-insensitive broadband achromatic metalens for mid-wave infrared detector

被引:0
|
作者
Meng, Fan long [1 ,2 ]
Le Liu, Jia [2 ,3 ,4 ]
Yue, Jia Xin [2 ,3 ,4 ]
Qin, Le [2 ,3 ,4 ]
Zhang, Jin Yu [2 ,3 ,4 ]
Li, Xinxin [2 ,3 ,4 ]
Song, Cai Xia [2 ,3 ,4 ]
Zhang, Zhong Shan [2 ,3 ]
Chen, Hong [2 ,3 ,5 ]
Chang, Yu Chun [1 ]
Deng, Zhen [2 ,3 ,6 ]
机构
[1] Dalian Univ Technol, Sch Integrated Circuits, Dalian 116000, Peoples R China
[2] Chinese Acad Sci, Inst Phys, Key Lab Renewable Energy, Beijing Key Lab New Energy Mat & Devices,Beijing, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[4] Univ Chinese Acad Sci, Ctr Mat & Optoelect Engn, Beijing 100049, Peoples R China
[5] Songshan Lake Mat Lab, Dongguan 523808, Guangdong, Peoples R China
[6] Yangtze River Delta Phys Res Ctr, Liyang 213000, Jiangsu, Peoples R China
关键词
METASURFACE;
D O I
10.1364/OL.541487
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Metalenses, boasting outstanding focusing efficiency and high-resolution imaging capabilities, have generated widespread usage in fields such as integrated optics, achromatic imaging, and optical holography. In this study, we have developed a broadband achromatic metalens within the detection range from 3 to 5 mu m, and it has a numerical aperture (NA) of 0.71 with a remarkable maximum focusing efficiency of 63.8% at the focal plane within the specified bandwidth. We have further delved into the dispersion control mechanism that combines the geometric and transmission phases and optimized the constructed phase response simulation database using the particle swarm optimization (PSO) algorithm, ensuring a precise phase matching between the actual wavefront and the ideal focusing wavefront. This metalens with its ability to expand the array size has the potential to create a compact infrared imager, which holds significant importance in achieving efficient detection and integration within infrared detectors. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
引用
收藏
页码:5563 / 5566
页数:4
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