Evidence map›Paper›PMID 34795222›Full record

ArticleNature communications2021

Multispecies and individual gas molecule detection using Stokes solitons in a graphene over-modal microresonator.

Teng Tan, Zhongye Yuan, Hao Zhang, Guofeng Yan, Siyu Zhou, Ning An, Bo Peng, Giancarlo Soavi, Yunjiang Rao, Baicheng Yao

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  10. Functionalized Optical Microcavities for Sensing Applications.Nanomaterials (Basel, Switzerland) · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Multimode sensing based on optical microcavities.Frontiers of optoelectronics · 2023
    Review
  19. Direct tuning of soliton detuning in an ultrahigh-Nanophotonics (Berlin, Germany) · 2023
    Article
  20. 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

10 authors.

Teng Tan *Key Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China.ORCID http://orcid.org/0000-0003-1820-3618
Zhongye Yuan *Key Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China.
Hao Zhang *Key Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China.
Guofeng YanResearch Centre of Optical Fiber Sensing, Zhejiang Laboratory, Hangzhou, 310000, China.
Siyu ZhouState Key Laboratory of Electronic Thin Film and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Ning AnKey Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China.
Bo PengState Key Laboratory of Electronic Thin Film and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, China.ORCID http://orcid.org/0000-0001-9411-716X
Giancarlo SoaviInstitute of Solid State Physics, Friedrich Schiller University Jena, Jena, 07743, Germany. giancarlo.soavi@uni-jena.de.ORCID http://orcid.org/0000-0003-2434-2251
Yunjiang RaoKey Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China. yjrao@uestc.edu.cn.ORCID http://orcid.org/0000-0003-0717-5586
Baicheng YaoKey Laboratory of Optical Fiber Sensing and Communications (Education Ministry of China), University of Electronic Science and Technology of China, Chengdu, 611731, China. yaobaicheng@uestc.edu.cn.ORCID http://orcid.org/0000-0001-8368-5815

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) CRC 1375 NOA project B5EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) GrapheneCore3 881603National Science Foundation of China | Major Research Plan 61975025
6 · The paper itself

Abstract

Soliton frequency combs generate equally-distant frequencies, offering a powerful tool for fast and accurate measurements over broad spectral ranges. The generation of solitons in microresonators can further improve the compactness of comb sources. However the geometry and the material's inertness of pristine microresonators limit their potential in applications such as gas molecule detection. Here, we realize a two-dimensional-material functionalized microcomb sensor by asymmetrically depositing graphene in an over-modal microsphere. By using one single pump, spectrally trapped Stokes solitons belonging to distinct transverse mode families are co-generated in one single device. Such Stokes solitons with locked repetition rate but different offsets produce ultrasensitive beat notes in the electrical domain, offering unique advantages for selective and individual gas molecule detection. Moreover, the stable nature of the solitons enables us to trace the frequency shift of the dual-soliton beat-note with uncertainty <0.2 Hz and to achieve real-time individual gas molecule detection in vacuum, via an optoelectronic heterodyne detection scheme. This combination of atomically thin materials and microcombs shows the potential for compact photonic sensing with high performances and offers insights toward the design of versatile functionalized microcavity photonic devices.

Identifiers

PMID34795222
PMCPMC8602637

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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.