基于智能算法的超材料快速优化设计方法研究进展

目前，超材料研究不断向工程化应用推进，在物理机理与效应、设计理论与方法、加工制备与测试等方面取得了突飞猛进的发展。但是，传统的超材料设计主要依赖人工设计和优化，面对大规模的工程化应用设计时，无法实现数量庞大的超材料结构单元的快速整体设计。近几年，涵盖传统启发式算法和神经网络算法的智能算法在超材料设计中所占的比重逐步上升...

Research Progress on Rapid Optimization Design Methods of Metamaterials Based on Intelligent Algorithms

At present,research on metamaterials is continuously advancing to engineering applications,and great progress is being achieved in the areas of physical mechanisms and effects,design theory and methods,and fabrication and measurement.However,traditional metamaterials design mainly relies on artificial design and optimization.In the face of large-scale engineering applications,it is impossible to realize the rapid overall design of a large number of metamaterial structural units.In recent years,the proportion of intelligent algorithms covering traditional heuristic algorithms and neural network algorithms in metamaterials design has increased gradually.Metamaterials design based on intelligent algorithms can surpass the limitation of traditional methods in different substrate systems,frequency variation,and different performance indicators,offering the unique advantages of rapid design and architectural innovation.This paper summarizes the application of several typical intelligent algorithms,including the genetic algorithm,Hopfield network algorithm,and deep learning algorithm in metamaterials design,which include forward designs and an inverse design.The use of intelligent algorithms can achieve the rapid design of frequency selective surfaces under different performance indexes,multi-mechanisms composite absorber metamaterials,flat focusing,and abnormal reflection metasurfaces,providing the necessary support for design methods while promoting the engineering applications of metamaterials.