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

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.