近日，美国康宁公司的Paulo Dainese及其研究小组与哈佛大学的Federico Capasso等人合作并取得一项新进展。经过不懈努力，他们对产生高效超表面形状优化技术的理论与实现进行研究。相关研究成果已于2024年10月29日在国际知名学术期刊《光：科学与应用》上发表。

本文通过数值与实验方法，展示了一种形状优化技术，该技术不仅能实现高效率的超表面设计，还能通过对表面梯度的傅里叶分解直接控制结构复杂度。所提出的方法为逆向设计的高效率超表面的可制造性开辟了道路。

据悉，复杂的非局域性行为给设计高效、多功能的超表面带来了巨大挑战。虽然采用超构原子库能提供一种简单快速的实现方法，但柱体间的相互作用往往会限制性能表现。而另一极端，基于拓扑优化的逆向设计虽然利用非局域耦合达到了高效率，却会产生结构复杂且难以制造的问题。

附：英文原文

Title: Shape optimization for high efficiency metasurfaces: theory and implementation

Author: Dainese, Paulo, Marra, Louis, Cassara, Davide, Portes, Ary, Oh, Jaewon, Yang, Jun, Palmieri, Alfonso, Rodrigues, Janderson Rocha, Dorrah, Ahmed H., Capasso, Federico

Issue&Volume: 2024-10-29

Abstract: Complex non-local behavior makes designing high efficiency and multifunctional metasurfaces a significant challenge. While using libraries of meta-atoms provide a simple and fast implementation methodology, pillar to pillar interaction often imposes performance limitations. On the other extreme, inverse design based on topology optimization leverages non-local coupling to achieve high efficiency, but leads to complex and difficult to fabricate structures. In this paper, we demonstrate numerically and experimentally a shape optimization method that enables high efficiency metasurfaces while providing direct control of the structure complexity through a Fourier decomposition of the surface gradient. The proposed method provides a path towards manufacturability of inverse-designed high efficiency metasurfaces.

DOI: 10.1038/s41377-024-01629-5

Source: https://www.nature.com/articles/s41377-024-01629-5