In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-...In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-demand customization for absorbers. The inverse design of absorption peak frequencies can be achieved from 0.5 to 10 terahertz(THz), covering the quasi-entire THz band. Based on this, the BDNN is extended to broadband absorption, and the inverse design yields an MMA at the desired frequency. This work provides a broadly applicable approach to the custom design of multifunctional devices that can facilitate the evaluation and design of metasurfaces in electromagnetic absorption.展开更多
基金supported by the National Natural Science Foundation of China (No. 61705058)。
文摘In this work, we propose a novel approach that combines a bidirectional deep neural network(BDNN) with a multifunctional metasurface absorber(MMA) for inverse design, which can effectively address the challenge of on-demand customization for absorbers. The inverse design of absorption peak frequencies can be achieved from 0.5 to 10 terahertz(THz), covering the quasi-entire THz band. Based on this, the BDNN is extended to broadband absorption, and the inverse design yields an MMA at the desired frequency. This work provides a broadly applicable approach to the custom design of multifunctional devices that can facilitate the evaluation and design of metasurfaces in electromagnetic absorption.
