Evidence map›Paper›PMID 39191869›Full record

ArticleScientific reports2024

Deep neural network-enabled multifunctional switchable terahertz metamaterial devices.

Jing Li, Rui Cai, Huanyang Chen, BinYi Ma, Qiannan Wu, Mengwei Li

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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.

Jing LiSchool of Instrument and Electronics, North University of China, Taiyuan, 030051, China.
Rui CaiSchool of Instrument and Electronics, North University of China, Taiyuan, 030051, China.
Huanyang ChenDepartment of Physics, Xiamen University, Xiamen, 361000, China.
BinYi MaSchool of Instrument and Electronics, North University of China, Taiyuan, 030051, China.
Qiannan WuSchool of Instrument and Intelligent Future Technology, North University of China, Taiyuan, 030051, China. qiannanwoo@nuc.edu.cn.
Mengwei LiSchool of Instrument and Electronics, North University of China, Taiyuan, 030051, China. lmwprew@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under the support of deep neural networks (DNN), a multifunctional switchable terahertz metamaterial (THz MMs) device is designed and optimized. This device not only achieves ideal ultra-wideband (UWB) absorption in the THz frequency range but enables dual-functional polarization transformation over UWB. When vanadium dioxide (VO

Indexed as

AbsorberDeep neural networks (DNN)Dual-wideband (UWB)MultifunctionalPolarization converter

Identifiers

PMID39191869
PMCPMC11349754

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.