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作 者:申益佳 谢鑫 蒲明博[1,2] 张飞 马晓亮 郭迎辉[1,2] 李雄 王长涛[1,2] 罗先刚 Shen Yijia;Xie Xin;Pu Mingbo;Zhang Fei;Ma Xiaoliang;Guo Yinghui;Li Xiong;Wang Changtao;Luo Xiangang(State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering,Institute of Optics and Electronics,Chinese Academy of Sciences,Chengdu,Sichuan 610209,China;School of Optoelectronics,Chinese Academy of Sciences,Beijing 100049,China;National Institute of Defense Technology Innovation,Academy of Military Sciences PLA China,Beijing 100071,China)
机构地区:[1]中国科学院光电技术研究所微细加工光学技术国家重点实验室,四川成都610209 [2]中国科学院大学光电学院,北京100049 [3]中国人民解放军军事科学院国防科技创新研究院,北京100071
出 处:《光电工程》2020年第10期108-116,共9页Opto-Electronic Engineering
基 金:国家自然科学基金资助项目(61822511,61675208)。
摘 要:超透镜是超表面在成像领域中具有较大应用潜力的平面光学器件,但限于色差和较窄的工作带宽,通常难以应用于彩色成像及显示技术。本文设计了一种相位调控型透射式超透镜,实现了400 nm^650 nm波段的宽带消色差聚焦功能,带宽范围内焦平面处的平均聚焦效率约为29%。该方法利用具有低损耗、高折射率优势的二氧化钛(TiO2)介质柱结构,在可见光波段内获得了类似截断波导产生的传输相位响应。同时分析了几何相位和传输相位相结合的色散调控机制,并使用粒子群算法对构建的相位响应仿真数据库进行优化,完成了实际波面与理想聚焦波面的相位匹配。设计的宽带消色差器件有望在显微成像、计算机视觉和机器视觉等领域发挥作用。Metalens is considered as one of the most promising planar optical devices composed of the metasurface, but it is usually difficult to realize full-color imaging and display due to the narrow working bandwidth and large chromatic aberration. In this paper, a phase-controlled transmissive metalens is designed to realize the broadband achromatic focusing within 400 nm^650 nm, and the average focusing efficiency is about 29% at the focal plane within the bandwidth range. The titanium dioxide(TiO2) dielectric nanopillar with low loss and high refractive index as a truncated waveguide can control the propagation phase in the visible. At the same time, we analyze the dispersion modulation mechanism which merges the geometric and propagation phases, and the particle swarm optimization(PSO) algorithm is used to optimize the phase response database, and accomplish the phase matching between the ideal and actual wavefronts. The proposed broadband achromatic devices may broaden the applications of metalens in micro-imaging, computer vision, and machine vision.
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