Accelerating optimization of terahertz metasurface design using principal component analysis in conjunction with deep learning networks-Reference-Cited by-同舟云学术

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Accelerating optimization of terahertz metasurface design using principal component analysis in conjunction with deep learning networks

Published:2024-10 Issue: Volume:66 Page:102452
ISSN:1874-4907
Container-title:Physical Communication
language:en
Short-container-title:Physical Communication

Author:

Ding Kaige^ORCID,Zhao Zhinan,Ma Siyuan,Qiu Yanqing,Lang Tingting^ORCID,Chen Ting^ORCID

Publisher

Elsevier BV

Reference34 articles.

1. Flexible graphene-based metamaterial sensor for highly sensitive detection of bovine serum albumin;Xiao;Appl. Opt.,2022

2. High-Q Fano terahertz resonance based on bound states in the continuum in all-dielectric metasurface;Cen;Appl. Surf. Sci.,2022

3. Sensitive detection of aspartame and vanillin by combining terahertz fingerprinting with a metamaterial;Zhang;IEEE Sens. J.,2022

4. All-metal terahertz metamaterial biosensor for protein detection;Wang;Nanoscale Res. Lett.,2021

5. High-sensitivity temperature sensor based on the perfect metamaterial absorber in the terahertz band;Wang,2023

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