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.
作者
马文壮
游可唯
张胤
周阳
张丽
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)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
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)。
关键词
人工智能
深度学习
微纳结构
光谱设计
artificial intelligence
deep learning
micro-nano structures
spectral design
