Evidence map›Paper›PMID 36505923›Full record

ArticleiScience2022

A cantilever-structure triboelectric nanogenerator for energy harvesting and defect detection via long short-term memory network.

Chuanfu Xin, Zifeng Xu, Ying Gong, Hengyu Guo, Zhongjie Li, Jiheng Ding, Shaorong Xie

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2022. 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

7 authors.

Chuanfu XinSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China.
Zifeng XuSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China.
Ying GongSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China.
Hengyu GuoDepartment of Applied Physics, Chongqing University, Chongqing 400044, P.R. China.
Zhongjie LiSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China.
Jiheng DingSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, P.R. China.
Shaorong XieSchool of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The electric signals of cantilever energy harvesting devices with/without a crack were mainly obtained by external sensors, so detecting device damage on a large scale is difficult. To tackle the issue, a cantilever-structure freestanding triboelectric nanogenerator (CSF-TENG) device was proposed, which can scavenge ambient energy and act as a self-powered sensor. Firstly, the relation between the peak-to-peak voltage and amplitude of the CSF-TENG was established. Next, the output performance of the CSF-TENG was measured. Then, depending on electric signals output by the CSF-TENG, a cantilever defect identification model was built by using the wavelet packet and long short-term memory (LSTM) algorithms. The experimental results manifest that the accuracy of the model is about 98.6%. Thus, the CSF-TENG with a crack can be detected timely due to its self-monitoring ability, which is of great significance for the development of self-powered sensor networks.

Indexed as

Energy materialsMaterials chemistryMaterials science

Identifiers

PMID36505923
PMCPMC9730220

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.