Evidence map›Paper›PMID 32899753›Full record

ArticlePolymers2020

Long-Period Fiber Grating Sensor Based on a Conductive Polymer Functional Layer.

Ching-Yu Hsu, Chia-Chin Chiang, Hsin-Yi Wen, Jian-Jie Weng, Jing-Lun Chen, Tao-Hsing Chen, Ya-Hui Chen

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Ching-Yu HsuDepartment of Marine Mechanical Engineering, R.O.C. Naval Academy, Kaohsiung 81345, Taiwan.ORCID 0000-0002-4012-8274
Chia-Chin ChiangDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.ORCID 0000-0003-2809-913X
Hsin-Yi WenDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.
Jian-Jie WengDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.
Jing-Lun ChenDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.
Tao-Hsing ChenDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.ORCID 0000-0002-5433-1812
Ya-Hui ChenDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan.

Funding

Ministry of Science and Technology MOST-107-2221-E-992 -043 -MY3
6 · The paper itself

Abstract

A temperature sensor was fabricated with a functional conductive poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) coating on a long-period fiber grating (LPFG). The LPFG was fabricated by laser-assisted wet-chemical etching for controlling the grating depth of the LPFG after the treated surface of an optical fiber was inscribed by laser light. The functional conductive polymer acts as a temperature sustained sensing layer and enhances the grating depth of the LPFG sensor as a strain buffer at various temperatures. The sensor was subjected to three cycles of temperature measurement to investigate the sensor's wavelength shift and energy loss when exposed to temperatures between 30 and 100 °C. Results showed that the sensor's average wavelength sensitivity and its linearity were 0.052 nm/°C and 99%, respectively; average transmission sensitivity and linearity were 0.048 (dB/°C) and 95%, respectively.

Indexed as

fiber sensorlaser-assisted-etching LPFG (LLPFG)long-period fiber grating (LPFG)PEDOT:PSStemperature detection

Identifiers

PMID32899753
PMCPMC7564938

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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.