多路复用
计算机科学
迭代和增量开发
极化(电化学)
设计过程
工程设计过程
制作
计算机工程
材料科学
电子工程
纳米技术
在制品
机械工程
工程类
电信
病理
物理化学
软件工程
化学
医学
替代医学
运营管理
作者
Sensong An,Bowen Zheng,Hong Tang,Mikhail Y. Shalaginov,L. P. Zhou,Hang Li,Myungkoo Kang,Myungkoo Kang,Tian Gu,Juejun Hu,Clayton Fowler,Hualiang Zhang
标识
DOI:10.1002/adom.202001433
摘要
Abstract Metasurfaces have enabled precise electromagnetic (EM) wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices. These advantages in precision and functionality come at the cost of tremendous difficulty in finding individual meta‐atom structures based on specific requirements (commonly formulated in terms of EM responses), which makes the design of multifunctional metasurfaces a key challenge in this field. In this paper, a generative adversarial network that can tackle this problem and generate meta‐atom/metasurface designs to meet multifunctional design goals is presented. Unlike conventional trial‐and‐error or iterative optimization design methods, this new methodology produces on‐demand free‐form structures involving only a single design iteration. More importantly, the network structure and the robust training process are independent of the complexity of design objectives, making this approach ideal for multifunctional device design. Additionally, the ability of the network to generate distinct classes of structures with similar EM responses but different physical features can provide added latitude to accommodate other considerations such as fabrication constraints and tolerances. The network's ability to produce a variety of multifunctional metasurface designs is demonstrated by presenting a bifocal metalens, a polarization‐multiplexed beam deflector, a polarization‐multiplexed metalens, and a polarization‐independent metalens.
科研通智能强力驱动
Strongly Powered by AbleSci AI