Evidence map›Paper›PMID 29773860›Full record

ArticleScientific reports2018

Noninvasive low-cycle fatigue characterization at high depth with photoacoustic eigen-spectrum analysis.

Xiaoxiang Gao, Chao Tao, Rong Zhu, Xiaojun Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Xiaoxiang GaoMOE Key Laboratory of Modern Acoustics, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China.
Chao TaoMOE Key Laboratory of Modern Acoustics, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China. taochao@nju.edu.cn.
Rong ZhuDepartment of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
Xiaojun LiuMOE Key Laboratory of Modern Acoustics, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China. liuxiaojun@nju.edu.cn.ORCID 0000-0002-7826-9742

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, photoacoustic eigen-spectrum analysis was proposed for noninvasively characterizing the mechanical properties of materials. We theoretically predicted the relationship between the photoacoustic eigen-spectra of cylindrical optical absorbers and their mechanical properties. Experimental measurements of eigen-spectra extracted from photoacoustic coda waves agreed well with the theoretical predictions. We then applied the photoacoustic eigen-spectrum analysis for contactless monitoring of low-cycle fatigue damage. Experiments showed that the photoacoustic eigen-spectra were closely related to the degree of low-cycle fatigue. This study might enhance the contrast of photoacoustic imaging ford mechanical characterization.

Identifiers

PMID29773860
PMCPMC5958075

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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.