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Realizing Multi-Absorption Properties Metamaterial Absorbers by a Dual-Channel Tandem Neural Network

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Abstract

Deep learning-based research on metamaterial absorbers (MAs) has received increasing attention. However, the problem of homogeneity of structure and material of MAs has constrained their further development. In this paper, we designed MA with a top metal layer consisting of eight rectangular nano-rods, and adjusting their lengths can form various structures. In addition, we formed a material database for constructing MAs with the results of random combinations of eight materials and represented them in a coded manner. Meanwhile, we design MAs with ultra-wideband and dual absorption bandwidths using a dual-channel tandem neural network (DTNN). Compared with the existing methods, our method not only simplifies the steps of selecting materials and structures but also enables the design of MAs with different absorption properties.

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No datasets were generated or analyzed during the current study.

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Funding

This work has been supported by National Natural Science Foundation of China (grant nos. 62175070 and 61875057); GuangDong Basic and Applied Basic Research Foundation (grant nos. 2021A1515010352, 2021A1515012652, and 2023A1515012966); and The Science and Technology Program of Guangzhou (grant no. 202201010340).

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Authors and Affiliations

  1. Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou, 510006, China

    Shuqin Wang, Qiongxiong Ma, Zhongchao Wei, Wanrong Liu, Ruihuan Wu & Jian** Guo

  2. Guangdong Provincial Key Laboratory of Antenna and Radio Frequency Technology, Guangdong Shenglu Telecommunication Tech. Co., Ltd, Foshan, 430072, Guangdong, China

    Wen Ding

  3. Guangdong Education Center of Optoelectronic Information Technology, South China Normal University, Guangzhou, 510006, China

    Jian** Guo

Authors
  1. Shuqin Wang
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  2. Qiongxiong Ma
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  3. Zhongchao Wei
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  4. Wanrong Liu
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  5. Ruihuan Wu
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  6. Wen Ding
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  7. Jian** Guo
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Contributions

Shuqin Wang, Qiongxiong Ma, Zhongchao Wei, Wanrong Liu, Ruihuan Wu, Wen Ding, and Jian** Guo contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Shuqin Wang. Shuqin Wang wrote the main manuscript text. Data acquisition was performed by Shuqin Wang, Qiongxiong Ma, and Jian** Guo. Jian** Guo supervised the project. The investigation and software were performed by Shuqin Wang, Qiongxiong Ma, Zhongchao Wei, Wanrong Liu, Ruihuan Wu, Wen Ding, and Jian** Guo. Funding acquisition was provided by Zhongchao Wei, Ruihuan Wu, and Qiongxiong Ma. All authors reviewed the manuscript.

Corresponding author

Correspondence to Jian** Guo.

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Wang, S., Ma, Q., Wei, Z. et al. Realizing Multi-Absorption Properties Metamaterial Absorbers by a Dual-Channel Tandem Neural Network. Plasmonics (2023). https://doi.org/10.1007/s11468-023-02177-1

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