Evidence map›Paper›PMID 38698124›Full record

ArticleScientific reports2024

Polarization-insensitive perfect absorption in van der waals hyper-structure.

Muhammad Imran, Muhyiddeen Yahya Musa, Sajid Rauf, Dajiang Lu, Rujiang Li, Yibin Tian

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Muhammad Imran *College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518000, China.
Muhyiddeen Yahya Musa *Department of Agriculture and Bio-Environmental Engineering Technology, Audu Bako College of Agriculture Dambatta, Kano, Nigeria.
Sajid RaufCollege of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518000, China.
Dajiang LuCollege of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518000, China.
Rujiang LiNational Key Laboratory of Radar Detection and Sensing, School of Electronic Engineering, Xidian University, Xi'an, 710071, China. rujiangli@xidian.edu.cn.
Yibin TianCollege of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518000, China. ybtian@szu.edu.cn.

Funding

National Natural Science Foundation of China 12104353Shenzhen University 86901/010211
6 · The paper itself

Abstract

Infrared perfect absorption has been widely investigated due to its potential applications in photodetectors, photovoltaics and medical diagnostics. In this report, we demonstrate that at particular infrared frequencies, a simple planar structure made up of graphene-hexagonal Boron Nitride (hBN) hyper-structure is able to nearly perfectly absorb incident light irrespective of its polarization (Transverse-Magnetic TM, or Transverse-Electric TE). By using this interferenceless technique, the hyper-structure achieves nearly zero reflectance at a wide range of angles in a narrow frequency band. We analytically predict the condition of achieving such an important feature of perfect absorption for both TM and TE polarizations. Interestingly, the infrared perfect absorption can be redshifted by increasing the thickness of the hBN layers and blueshifted by increasing the graphene's chemical potential. Such flexible control of infrared perfect absorption offers a new tool for controlling electromagnetic waves and has potential applications in photodetection and other light control applications.

Indexed as

GrapheneHexagonal Boron Nitride (hBN)Hyper-structureInfrared perfect absorptionPolarization

Identifiers

PMID38698124
PMCPMC11066130

What OpenQuestion holds

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Registered trials

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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.