Knowledge Management System Of Institute of process engineering,CAS
| Visible Achromatic Metalens Design Based on Artificial Neural Network | |
| Wang, Feilou1; Geng, Guangzhou2; Wang, Xueqian3; Li, Junjie2; Bai, Yang3; Li, Jianqiang4,6; Wen, Yongzheng1; Li, Bo5; Sun, Jingbo1; Zhou, Ji1 | |
| 2021-11-23 | |
| Source Publication | ADVANCED OPTICAL MATERIALS
 |
| ISSN | 2195-1071 |
| Pages | 8 |
| 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. |
| Keyword | achromatic focusing metalenses neural networks visible wavelength |
| DOI | 10.1002/adom.202101842 |
| Language | 英语 |
| WOS Keyword | DIELECTRIC METASURFACES ; RESOLUTION ; PHASE ; POLARIZATION |
| Funding Project | Basic Science Center Project of NSFC[51788104] ; National Natural Science Foundation of China[11974203] ; National Natural Science Foundation of China[12074420] ; National Natural Science Foundation of China[52072203] ; Beijing Municipal Science and Technology Project[Z191100004819002] ; National Key Research and Development Program of China[2016YFA0200800] |
| WOS Research Area | Materials Science ; Optics |
| WOS Subject | Materials Science, Multidisciplinary ; Optics |
| Funding Organization | Basic Science Center Project of NSFC ; National Natural Science Foundation of China ; Beijing Municipal Science and Technology Project ; National Key Research and Development Program of China |
| WOS ID | WOS:000721792600001 |
| Publisher | WILEY-V C H VERLAG GMBH |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ipe.ac.cn/handle/122111/51129 |
| Collection | 中国科学院过程工程研究所 |
| Corresponding Author | Li, Junjie; Bai, Yang; Sun, Jingbo; Zhou, Ji |
| Affiliation | 1.Tsinghua Univ, State Key Lab New Ceram & Fine Proc, Sch Mat Sci & Engn, Beijing 100084, Peoples R China 2.Chinese Acad Sci, Beijing Natl Lab Condensed Matter Phys, Inst Phys, Beijing 100190, Peoples R China 3.Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, Inst Adv Mat & Technol, Beijing 100083, Peoples R China 4.Chinese Acad Sci, CAS Key Lab Green Proc & Engn, Natl Engn Lab Hydromet Cleaner Prod Technol, Inst Proc Engn, Beijing 100190, Peoples R China 5.Tsinghua Shenzhen Int Grad Sch Shenzhen, Inst Mat Res, Shenzhen 518055, Peoples R China 6.Univ Sci & Technol Beijing, Sch Mat Sci & Engn, Beijing 100083, Peoples R China |
| Recommended Citation GB/T 7714 | Wang, Feilou,Geng, Guangzhou,Wang, Xueqian,et al. Visible Achromatic Metalens Design Based on Artificial Neural Network[J]. ADVANCED OPTICAL MATERIALS,2021:8. |
| APA | Wang, Feilou.,Geng, Guangzhou.,Wang, Xueqian.,Li, Junjie.,Bai, Yang.,...&Zhou, Ji.(2021).Visible Achromatic Metalens Design Based on Artificial Neural Network.ADVANCED OPTICAL MATERIALS,8. |
| MLA | Wang, Feilou,et al."Visible Achromatic Metalens Design Based on Artificial Neural Network".ADVANCED OPTICAL MATERIALS (2021):8. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment