Cargando…
Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management
Infrared (IR) stealth plays a vital role in the modern military field. With the continuous development of detection technology, multi-band (such as near-IR laser and middle-IR) compatible IR stealth is required. Combining rigorous coupled wave analysis (RCWA) with Deep Learning (DL), we design a Ge/...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058171/ https://www.ncbi.nlm.nih.gov/pubmed/36985924 http://dx.doi.org/10.3390/nano13061030 |
_version_ | 1785016557870514176 |
---|---|
author | Wang, Lei Dong, Jian Zhang, Wenjie Zheng, Chong Liu, Linhua |
author_facet | Wang, Lei Dong, Jian Zhang, Wenjie Zheng, Chong Liu, Linhua |
author_sort | Wang, Lei |
collection | PubMed |
description | Infrared (IR) stealth plays a vital role in the modern military field. With the continuous development of detection technology, multi-band (such as near-IR laser and middle-IR) compatible IR stealth is required. Combining rigorous coupled wave analysis (RCWA) with Deep Learning (DL), we design a Ge/Ag/Ge multilayer circular-hole metasurface capable of multi-band IR stealth. It achieves low average emissivity of 0.12 and 0.17 in the two atmospheric windows (3~5 μm and 8~14 μm), while it achieves a relatively high average emissivity of 0.61 between the two atmospheric windows (5~8 μm) for the purpose of radiative thermal management. Additionally, the metasurface has a narrow-band high absorptivity of 0.88 at the near-infrared wavelength (1.54 μm) for laser guidance. For the optimized structure, we also analyze the potential physical mechanisms. The structure we optimized is geometrically simple, which may find practical applications aided with advanced nano-fabrication techniques. Also, our work is instructive for the implementation of DL in the design and optimization of multifunctional IR stealth materials. |
format | Online Article Text |
id | pubmed-10058171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100581712023-03-30 Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management Wang, Lei Dong, Jian Zhang, Wenjie Zheng, Chong Liu, Linhua Nanomaterials (Basel) Article Infrared (IR) stealth plays a vital role in the modern military field. With the continuous development of detection technology, multi-band (such as near-IR laser and middle-IR) compatible IR stealth is required. Combining rigorous coupled wave analysis (RCWA) with Deep Learning (DL), we design a Ge/Ag/Ge multilayer circular-hole metasurface capable of multi-band IR stealth. It achieves low average emissivity of 0.12 and 0.17 in the two atmospheric windows (3~5 μm and 8~14 μm), while it achieves a relatively high average emissivity of 0.61 between the two atmospheric windows (5~8 μm) for the purpose of radiative thermal management. Additionally, the metasurface has a narrow-band high absorptivity of 0.88 at the near-infrared wavelength (1.54 μm) for laser guidance. For the optimized structure, we also analyze the potential physical mechanisms. The structure we optimized is geometrically simple, which may find practical applications aided with advanced nano-fabrication techniques. Also, our work is instructive for the implementation of DL in the design and optimization of multifunctional IR stealth materials. MDPI 2023-03-13 /pmc/articles/PMC10058171/ /pubmed/36985924 http://dx.doi.org/10.3390/nano13061030 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Lei Dong, Jian Zhang, Wenjie Zheng, Chong Liu, Linhua Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title | Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title_full | Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title_fullStr | Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title_full_unstemmed | Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title_short | Deep Learning Assisted Optimization of Metasurface for Multi-Band Compatible Infrared Stealth and Radiative Thermal Management |
title_sort | deep learning assisted optimization of metasurface for multi-band compatible infrared stealth and radiative thermal management |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058171/ https://www.ncbi.nlm.nih.gov/pubmed/36985924 http://dx.doi.org/10.3390/nano13061030 |
work_keys_str_mv | AT wanglei deeplearningassistedoptimizationofmetasurfaceformultibandcompatibleinfraredstealthandradiativethermalmanagement AT dongjian deeplearningassistedoptimizationofmetasurfaceformultibandcompatibleinfraredstealthandradiativethermalmanagement AT zhangwenjie deeplearningassistedoptimizationofmetasurfaceformultibandcompatibleinfraredstealthandradiativethermalmanagement AT zhengchong deeplearningassistedoptimizationofmetasurfaceformultibandcompatibleinfraredstealthandradiativethermalmanagement AT liulinhua deeplearningassistedoptimizationofmetasurfaceformultibandcompatibleinfraredstealthandradiativethermalmanagement |