Evidence map›Paper›PMID 39431093›Full record

ArticleACS omega2024

Self-Supplying Photovoltaic-Hygroelectric Coupling System Powering Internet of Things Sensors.

Changbao Xu, Xiang Zhang, Jiahao Fang, Yuming Yao, Yong Zhang, Xulei Lu, Tingting Yang, Mingyong Xin

Abstract read
In one paragraph

Article in ACS omega, 2024. 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

8 authors.

Changbao XuElectric Power Research Institute of Guizhou Power Grid Company Limited, Guiyang 550002, China.
Xiang ZhangTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.ORCID https://orcid.org/0009-0000-8761-7502
Jiahao FangTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Yuming YaoTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Yong ZhangTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Xulei LuTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Tingting YangTribology Research Institute, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Mingyong XinElectric Power Research Institute of Guizhou Power Grid Company Limited, Guiyang 550002, China.ORCID https://orcid.org/0000-0002-7521-6362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid advancement in the Internet of Things (IoT) has prompted a proliferation of sensor applications with increasing focus on harnessing environmental energy sources for powering these sensors. However, owing to the variability inherent in climatic and geographic conditions, a singular approach to environmental energy harvesting often fails to deliver sustainable and reliable power. Hygroelectric technology, leveraging the electrical coupling between nanostructured materials and water to convert moisture-derived energy into electricity, complements the advantages of light energy collection technology. In this study, an ion diode moisture-based power generation array was fabricated to yield an open-circuit voltage of 8 V and a short-circuit current of 3 mA under an 86.9% relative humidity (RH). Subsequently, integration of a photovoltaic module with the hygroelectric generator assembly via an energy management circuit augmented the system's overall power generation, manifesting a remarkable 1150% increase over the original moisture-based power generation configuration. Furthermore, the incorporation of such a hybridized system bolstered the operational efficiency, extending the duration of continuous power supply cycles by up to 78.2% in comparison with the control group with no moisture-derived energy input. This pioneering endeavor unveils a novel light-moisture coupling energy-harvesting paradigm tailored for sustaining uninterrupted power provision in wireless sensor network nodes, and the harvesting of one energy source is not affected by the other energy source at all. With its inherent adaptability, this approach holds promise for deployment in outdoor environments characterized by low illumination levels and high humidity, presenting a versatile solution to address sensor powering challenges.

Identifiers

PMID39431093
PMCPMC11483385

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LicenceCC BY-NC-ND
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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.