基于深度学习的微纳结构光谱设计研究进展OA北大核心CSTPCD

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.