Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface

doi:10.1088/1674-1056/adb94a

中国物理B ›› 2025, Vol. 34 ›› Issue (5): 50702-050702.doi: 10.1088/1674-1056/adb94a

Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface

Haolin Yang(杨昊霖)¹, Bo Ni(倪波)¹, Junhong Guo(郭俊宏)², Hua Zhou(周华)^1,†, and Jianhua Chang(常建华)¹

1 Jiangsu Key Laboratory of Meteorological Observation and Information Processing, School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2 College of Electronic and Optical Engineering and College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China

收稿日期:2024-12-06 修回日期:2025-02-05 接受日期:2025-02-24 出版日期:2025-05-15 发布日期:2025-04-24
通讯作者: Hua Zhou E-mail:hzhou@nuist.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 62375137 and 62175114).

Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface

Haolin Yang(杨昊霖)¹, Bo Ni(倪波)¹, Junhong Guo(郭俊宏)², Hua Zhou(周华)^1,†, and Jianhua Chang(常建华)¹

1 Jiangsu Key Laboratory of Meteorological Observation and Information Processing, School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2 College of Electronic and Optical Engineering and College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Received:2024-12-06 Revised:2025-02-05 Accepted:2025-02-24 Online:2025-05-15 Published:2025-04-24
Contact: Hua Zhou E-mail:hzhou@nuist.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 62375137 and 62175114).

摘要/Abstract

摘要： Structural colors based on metasurfaces have very promising applications in areas such as optical image encryption and color printing. Herein, we propose a deep learning-enabled reverse design of polarization-selective structural color based on coding metasurface. In this study, the long short-term memory (LSTM) neural network is presented to enable the forward and inverse mapping between coding metasurface structure and corresponding color. The results show that the method can achieve 98% accuracy for the forward prediction of color and 93% accuracy for the inverse design of the structure. Moreover, a cascaded architecture is adopted to train the inverse neural network model, which can solve the non-uniqueness problem of the polarization-selective color reverse design. This study provides a new path for the application and development of structural colors.

关键词: deep learning, inverse design, coding metasurface, structural color, polarization-selective

Abstract: Structural colors based on metasurfaces have very promising applications in areas such as optical image encryption and color printing. Herein, we propose a deep learning-enabled reverse design of polarization-selective structural color based on coding metasurface. In this study, the long short-term memory (LSTM) neural network is presented to enable the forward and inverse mapping between coding metasurface structure and corresponding color. The results show that the method can achieve 98% accuracy for the forward prediction of color and 93% accuracy for the inverse design of the structure. Moreover, a cascaded architecture is adopted to train the inverse neural network model, which can solve the non-uniqueness problem of the polarization-selective color reverse design. This study provides a new path for the application and development of structural colors.

Key words: deep learning, inverse design, coding metasurface, structural color, polarization-selective

中图分类号: (Neural networks, fuzzy logic, artificial intelligence)

07.05.Mh

78.20.Bh (Theory, models, and numerical simulation) 78.67.Pt (Multilayers; superlattices; photonic structures; metamaterials) 42.79.-e (Optical elements, devices, and systems)

Haolin Yang(杨昊霖), Bo Ni(倪波), Junhong Guo(郭俊宏), Hua Zhou(周华), and Jianhua Chang(常建华). Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface[J]. 中国物理B, 2025, 34(5): 50702-050702.

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Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface

Deep learning-enabled inverse design of polarization-selective structural color based on coding metasurface

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