DataVXAdvanced Optical MaterialsPaper
journal article·2022-02

Visible Achromatic Metalens Design Based on Artificial Neural Network

Feilou Wang, Guangzhou Geng, Xueqian Wang, Junjie Li, Yang Bai, Jianqiang Li, Yongzheng Wen, Bo Li, Jingbo Sun, Ji Zhou

Advanced Optical Materials· Volume 10· Issue 3
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Source abstract

Abstract

Abstract Metasurfaces, known as ultra‐thin and planar structures, are widely used in optical components with their excellent ability to manipulate the wavefront of the light. The key function of the metasurfaces is the spatial phase modulation, originated from the meta‐atoms. Thus, to find the relation between the phase modulation and the parameters of an individual meta‐atom, including the sizes, shapes, and material's optical properties, is the most important but also time‐consuming part in the metasurface design. Here by developing a backpropagation neural network based machine learning tool, the design process of a high performance achromatic metalens can be greatly simplified and accelerated. A library of the phase modulation data from 15 753 meta‐atoms can be generated in less than 1 s by our backpropagation neural network. In the experiment, it is demonstrated that the designed metalens shows an excellent achromatic focusing and imaging ability in the visible wavelengths from 420 to 640 nm without the polarization dependence.
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Research context

OpenAlex topics: Metamaterials and Metasurfaces Applications · Advanced Antenna and Metasurface Technologies · Photonic Crystals and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China

Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing 100190 China

Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing 100083 China

CAS Key Laboratory of Green Process and Engineering National Engineering Laboratory for Hydrometallurgical Cleaner Production Technology Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China

School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China

Institute of Materials Research Tsinghua Shenzhen International Graduate School Shenzhen Shenzhen 518055 China

Funding

National Natural Science Foundation of China · National Key Research and Development Program of China

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