Evidence map›Paper›PMID 37019920›Full record

ArticleNature communications2023

Imaging-based intelligent spectrometer on a plasmonic rainbow chip.

Dylan Tua, Ruiying Liu, Wenhong Yang, Lyu Zhou, Haomin Song, Leslie Ying, Qiaoqiang Gan

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Topological nanorainbow laser.Science advances · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Advances in Miniaturized Computational Spectrometers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
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

7 authors.

Dylan Tua *Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Ruiying Liu *Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Wenhong Yang *Material Science Engineering, Physical Science Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
Lyu ZhouElectrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Haomin SongMaterial Science Engineering, Physical Science Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.
Leslie YingElectrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.ORCID http://orcid.org/0000-0001-9801-1362
Qiaoqiang GanElectrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA. qiaoqiang.gan@kaust.edu.sa.ORCID http://orcid.org/0000-0001-8309-5081

Funding

King Abdullah University of Science and Technology (KAUST) BAS/1/1415-01-01King Abdullah University of Science and Technology (KAUST) REI/1/5232-01-01
6 · The paper itself

Abstract

Compact, lightweight, and on-chip spectrometers are required to develop portable and handheld sensing and analysis applications. However, the performance of these miniaturized systems is usually much lower than their benchtop laboratory counterparts due to oversimplified optical architectures. Here, we develop a compact plasmonic "rainbow" chip for rapid, accurate dual-functional spectroscopic sensing that can surpass conventional portable spectrometers under selected conditions. The nanostructure consists of one-dimensional or two-dimensional graded metallic gratings. By using a single image obtained by an ordinary camera, this compact system can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum. Assisted by suitably trained deep learning algorithms, we demonstrate the characterization of optical rotatory dispersion of glucose solutions at two-peak and three-peak narrowband illumination across the visible spectrum using just a single image. This system holds the potential for integration with smartphones and lab-on-a-chip systems to develop applications for in situ analysis.

Identifiers

PMID37019920
PMCPMC10076426

What OpenQuestion holds

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LicenceCC BY
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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.