Evidence map›Paper›PMID 41900259›Full record

ArticleMicromachines2026

Self-Regulating Wind Speed Adaptive Mode Switching for Efficient Wind Energy Harvesting Towards Self-Powered Wireless Sensing.

Ruifeng Li, Chenming Wang, Yiao Pan, Jianhua Zeng, Youchao Qi, Ping Zhang

Abstract read
In one paragraph

Article in Micromachines, 2026. 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. Review
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

6 authors.

Ruifeng LiSchool of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, No. 1 Jinji Road, Guilin 541004, China.
Chenming WangSchool of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, No. 1 Jinji Road, Guilin 541004, China.ORCID 0009-0003-9226-1821
Yiao PanSchool of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, No. 1 Jinji Road, Guilin 541004, China.
Jianhua ZengSchool of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, No. 1 Jinji Road, Guilin 541004, China.
Youchao QiCAS-Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, China.ORCID 0009-0004-0480-4580
Ping ZhangSchool of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, No. 1 Jinji Road, Guilin 541004, China.

Funding

Guangxi Natural Science Foundation 2025GXNSFBA069426
6 · The paper itself

Abstract

Wind energy harvesting based on triboelectric nanogenerators (TENGs) is a promising solution for powering distributed Internet of Things (IoT) nodes, yet its practical efficiency and stability are often hindered by the fluctuating and unpredictable nature of wind. Here, we propose a self-regulating TENG (SR-TENG) that leverages the synergistic effects of centrifugal, elastic, and frictional forces to automatically switch between non-contact and contact modes based on wind speed. This configuration achieves an ultra-low start-up wind speed of 0.86 m/s, ensures sustainable high-performance output across a broad wind speed range, and exhibits excellent durability with no observable performance degradation during 23,000 s of continuous operation at 375 rpm. Systematic structural optimization enables the SR-TENG to reach a peak open-circuit voltage of 140 V, a short-circuit current of 12.5 μA, and a transferred charge of 300 nC at 375 rpm. When integrated with a customized power management circuit, the system delivers a 30.39-fold increase in effective output power at a 1 MΩ load and a 4-fold faster charging rate for a 10 μF capacitor. For practical validation, the harvested ambient wind energy successfully powers a wireless temperature-humidity sensor for real-time cloud data transmission. These results highlight that the SR-TENG holds great potential for advanced wind energy harvesting and self-powered sensing applications in distributed IoT systems.

Indexed as

power management circuitself-regulating mechanismtriboelectric nanogeneratorwind energy harvestingwireless temperature-humidity sensing

Identifiers

PMID41900259
PMCPMC13029519

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.