Optimization of metamaterials and metamaterial-microcavity based on deep neural networks-Reference-Cited by-同舟云学术

Optimization of metamaterials and metamaterial-microcavity based on deep neural networks

Published:2022 Issue:23 Volume:4 Page:5137-5143
ISSN:2516-0230
Container-title:Nanoscale Advances
language:en
Short-container-title:Nanoscale Adv.

Author:

Lan Guoqiang¹²^ORCID,Wang Yu³^ORCID,Ou Jun-Yu³^ORCID

Affiliation:

1. School of Electronic Engineering, Heilongjiang University, No. 74 Xuefu Road, Harbin 150080, China

2. Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China

3. Optoelectronics Research Centre and Centre for Photonic Metamaterials, University of Southampton, Highfield, Southampton SO17 1BJ, UK

Abstract

We use a deep-learning method to optimize the design of split-ring metamaterials and metamaterial-microcavities. We use this method to quickly realize the design of the metamaterial-microcavity with the absorptance peak at 1310 nm.

Funder

Engineering and Physical Sciences Research Council

Heilongjiang University

Publisher

Royal Society of Chemistry (RSC)

Subject

General Engineering,General Materials Science,General Chemistry,Atomic and Molecular Physics, and Optics,Bioengineering

Link

http://pubs.rsc.org/en/content/articlepdf/2022/NA/D2NA00592A

Reference43 articles.

1. Metamaterial Electromagnetic Cloak at Microwave Frequencies

2. Flat optics with designer metasurfaces

3. An Overview of the Theory and Applications of Metasurfaces: The Two-Dimensional Equivalents of Metamaterials

4. Planar Metamaterial Analogue of Electromagnetically Induced Transparency for Plasmonic Sensing

5. Past achievements and future challenges in the development of three-dimensional photonic metamaterials

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