Evidence map›Paper›PMID 37686982›Full record

ArticleNanomaterials (Basel, Switzerland)2023

Quadruple Plasmon-Induced Transparency and Dynamic Tuning Based on Bilayer Graphene Terahertz Metamaterial.

Jiayu Zhang, Junyi Li, Shuxian Chen, Kunhua Wen, Wenjie Liu

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jiayu ZhangSchool of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Junyi LiSchool of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Shuxian ChenSchool of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Kunhua WenSchool of Physics and Optoelectronic Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Wenjie LiuInstitute of Advanced Photonics Technology, School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China.

Funding

The 2021 Characteristic Innovation Research Project for University Teachers 2021DZXX21The Engineering Research Center of Digital Imaging and Display, Ministry of Education, Soochow University SDGC2133The Guangdong Introducing Innovative and Entrepreneurial Teams of "The Pearl River Talent Recruitment Program" 2019ZT08X340The National Natural Science Foundation of China 62175039, U2001601, 62275054, 61975037The Natural Science Foundation of Guangdong Province 2023A1515010206
6 · The paper itself

Abstract

This study proposes a terahertz metamaterial structure composed of a silicon-graphene-silicon sandwich, aiming to achieve quadruple plasmon-induced transparency (PIT). This phenomenon arises from the interaction coupling of bright-dark modes within the structure. The results obtained from the coupled mode theory (CMT) calculations align with the simulations ones using the finite difference time domain (FDTD) method. Based on the electric field distributions at the resonant frequencies of the five bright modes, it is found that the energy localizations of the original five bright modes undergo diffusion and transfer under the influence of the dark mode. Additionally, the impact of the Fermi level of graphene on the transmission spectrum is discussed. The results reveal that the modulation depths (MDs) of 94.0%, 92.48%, 93.54%, 96.54%, 97.51%, 92.86%, 94.82%, and 88.20%, with corresponding insertion losses (ILs) of 0.52 dB, 0.98 dB, 1.37 dB, 0.70 dB, 0.43 dB, 0.63 dB, 0.16 dB, and 0.17 dB at the specific frequencies, are obtained, achieving multiple switching effects. This model holds significant potential for applications in versatile modulators and optical switches in the terahertz range.

Indexed as

Fermi levelgrapheneoptical switchplasmon-induced transparency

Identifiers

PMID37686982
PMCPMC10490479

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.