Evidence map›Paper›PMID 32927607›Full record

ReviewSensors (Basel, Switzerland)2020

Preparation and Application of Metal Nanoparticals Elaborated Fiber Sensors.

Jin Li, Haoru Wang, Zhi Li, Zhengcheng Su, Yue Zhu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. 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

5 authors.

Jin LiCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, China.ORCID 0000-0001-9658-8184
Haoru WangCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Zhi LiCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Zhengcheng SuCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Yue ZhuCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

Funding

111 Project B16009Fundamental Research Funds for Central Universities N2004007Joint Research Fund Liaoning-Shenyang National Laboratory for Materials Science 20180510015National Key R&D Program of China 2019YFB2006001Xi'an Science and Technology Plan 2020KJRC0133
6 · The paper itself

Abstract

In recent years, surface plasmon resonance devices (SPR, or named plamonics) have attracted much more attention because of their great prospects in breaking through the optical diffraction limit and developing new photons and sensing devices. At the same time, the combination of SPR and optical fiber promotes the development of the compact micro-probes with high-performance and the integration of fiber and planar waveguide. Different from the long-range SPR of planar metal nano-films, the local-SPR (LSPR) effect can be excited by incident light on the surface of nano-scaled metal particles, resulting in local enhanced light field, i.e., optical hot spot. Metal nano-particles-modified optical fiber LSPR sensor has high sensitivity and compact structure, which can realize the real-time monitoring of physical parameters, environmental parameters (temperature, humidity), and biochemical molecules (pH value, gas-liquid concentration, protein molecules, viruses). In this paper, both fabrication and application of the metal nano-particles modified optical fiber LSPR sensor probe are reviewed, and its future development is predicted.

Indexed as

fiber sensorsLSPRmetal nano-particlesplasmonics

Identifiers

PMID32927607
PMCPMC7570743

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.