Evidence map›Paper›PMID 35334736›Full record

ArticleMicromachines2022

An Automated Power Evaluation Workbench for Triboelectric Nanogenerators.

Ming Yuan, Chunhui Li, Sheng Zhang, Yannan Xie

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ming YuanCollege of Automation & Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.ORCID 0000-0001-7209-0357
Chunhui LiCollege of Automation & Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Sheng ZhangSuzhou Acoustic Technology Institute Co., Ltd., Changshu 215500, China.
Yannan XieState Key Laboratory of Organic Electronics and Information Displays, Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

Funding

National Natural Science Foundation of China 61701250, 61974071, 61601394Priority Academic Program Development of Jiangsu Higher Education Institutions PAPD, YX030003Start-Up Fund from Nanjing University of Posts and Telecommunications NY218151, NY218157the State Key Laboratory of Mechanical System and Vibration MSV202018
6 · The paper itself

Abstract

Triboelectric nanogenerators (TENGs) have high potential in self-powered sensing and energy harvesting applications. In general, TENGs' internal source resistance is high, and their output power varies under different load resistance values. Therefore, a resistance box is required to evaluate their energy harvesting performance and obtain the power curve under different load values. The load tuning process is usually performed by hand. This repetitive process is time-consuming and error-prone. Consequently, an Automated Power Evaluation Workbench (APEW) is developed, making the resistance switching and power measuring process program-controlled. The resistance value is resolved using the Octal decomposition principle. In addition, a resistance synthesis algorithm is proposed to alter the resistance value with a minimum step of 1 Ohm. The target resistance value is physically synthesized by relay switching, while digital lines control the relays. The proposed APEW is then evaluated experimentally, and the obtained results are compared with those of the traditional manual switching approach. It is deduced that the two power curves are almost identical. Therefore, it is believed that the proposed APEW will play a crucial role in TENG's further development.

Indexed as

automation testpower evaluationresistance synthesistriboelectric nanogenerator

Identifiers

PMID35334736
PMCPMC8955910

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.