Evidence map›Paper›PMID 36146295›Full record

ArticleSensors (Basel, Switzerland)2022

Ultra-High-Sensitivity, Miniaturized Fabry-Perot Interferometric Fiber-Optic Microphone for Weak Acoustic Signals Detection.

Guojie Wu, Haie Li, Hongxin Ye, Zhenfeng Gong, Junsheng Ma, Min Guo, Ke Chen, Wei Peng, Qingxu Yu, Liang Mei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Guojie WuSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Haie LiSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Hongxin YeSchool of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China.
Zhenfeng GongSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Junsheng MaSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Min GuoSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Ke ChenSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.ORCID 0000-0002-0495-2549
Wei PengSchool of Physics, Dalian University of Technology, Dalian 116024, China.
Qingxu YuSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.
Liang MeiSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China.ORCID 0000-0003-1000-4497

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An ultra-high-sensitivity, miniaturized Fabry-Perot interferometric (FPI) fiber-optic microphone (FOM) has been developed, utilizing a silicon cantilever as an acoustic transducer. The volumes of the cavity and the FOM are determined to be 60 microliters and 102 cubic millimeters, respectively. The FOM has acoustic pressure sensitivities of 1506 nm/Pa at 2500 Hz and 26,773 nm/Pa at 3233 Hz. The minimum detectable pressure (MDP) and signal-to-noise ratio (SNR) of the designed FOM are 0.93 μPa/Hz

Indexed as

Fabry-Perotfiber-optic microphone (FOM)weak acoustic signals detection

Identifiers

PMID36146295
PMCPMC9505396

What OpenQuestion holds

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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.