基于深度学习的微纳结构光谱设计研究进展  

Research Progress on Deep Learning-Based Spectral Design of Micro-Nano Structures

作　　者：马文壮 游可唯 张胤[1,2] 周阳[1,2] 张丽[1,2] MA Wenzhuang;YOU Kewei;ZHANG Yin;ZHOU Yang;ZHANG Li(National Engineering Research Center of Electromagnetic Radiation Control Materials,University of Electronic Science and Technology of China,Chengdu 611731,China;Key Laboratory of Multi-Spectral Absorbing Materials and Structures of Ministry of Education,University of Electronic Science and Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学国家电磁辐射控制材料工程技术研究中心,成都611731 [2]电子科技大学多频谱吸波材料与结构教育部重点实验室(B类),成都611731

出　　处：《电子科技大学学报》2024年第5期641-654,共14页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(52021001,52022018,52472147)。

摘　　要：随着人工智能技术的快速发展,深度学习在微纳结构光谱调控领域展现出了巨大的应用潜力。深度学习可以在无明确物理解析模型的情况下,通过构建复杂的神经网络,从实验或仿真数据中学习微纳结构的光谱响应特性,从而实现高效的设计优化,这为微纳结构的设计提供了一种新的思路和方法。该文综述了近年来深度学习在微纳结构设计中的研究进展,重点讨论了其在结构色、热辐射控制以及窄带光谱传感等光谱调控领域的应用,并展望了该领域未来的发展机遇与挑战。With the rapid development of artificial intelligence technology,deep learning has shown tremendous potential in the field of spectral regulation of micro-nano structures.By constructing complex neural network models,deep learning can learn the spectral response characteristics of micro-nano structures from experimental or simulation data without the need for explicit physical analytical models,thereby achieving efficient design optimization.This provides a new approach and methodology for the design of micro-nano structures.This paper reviews the recent research progress of deep learning in micro-nano structure design,focusing on its applications in structural color,thermal radiation control,and narrowband spectral sensing,and also discusses future opportunities and challenges in this field.

关 键 词：人工智能 深度学习 微纳结构 光谱设计 

分 类 号：TN213[电子电信—物理电子学] O43[机械工程—光学工程]