Evidence map›Paper›PMID 41903123›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Gecko-Like Multi-Directional High-Power Magneto-Mechano-Electric Energy Harvesters for Self-Powered, Hundred-Meter-Scale LoRa Communication.

Shitong Fang, Haoxian Peng, Mingjing Cai, Liuchao Jin, Yuelong Yu, Mianxin Xiao, Qingyang Xu, Jiacheng Hou, Degui Yu, Zhihui Lai and 4 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

14 authors.

Shitong FangGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.ORCID https://orcid.org/0000-0002-4813-3027
Haoxian PengGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.
Mingjing CaiGuangzhou Institute of Technology and School of Mechano-Electronic Engineering, Xidian University, Guangzhou, China.
Liuchao JinDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-6204-1922
Yuelong YuGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.
Mianxin XiaoGuangzhou Institute of Technology and School of Mechano-Electronic Engineering, Xidian University, Guangzhou, China.
Qingyang XuInstitute of Artificial Intelligence, School of Future Technology, Shanghai University, Shanghai, China.
Jiacheng HouInstitute of Artificial Intelligence, School of Future Technology, Shanghai University, Shanghai, China.
Degui YuGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.
Zhihui LaiGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.ORCID https://orcid.org/0000-0003-4729-9604
Xin LiGuangzhou Institute of Technology and School of Mechano-Electronic Engineering, Xidian University, Guangzhou, China.
Shuxiang DongGuangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China.ORCID https://orcid.org/0000-0002-9617-6013
Biao WangInstitute of Artificial Intelligence, School of Future Technology, Shanghai University, Shanghai, China.ORCID https://orcid.org/0000-0002-2746-8207
Wei-Hsin LiaoDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-7221-5906

Funding

Chinese University of Hong Kong 4055178General Projects of Natural Science Foundation of Shanghai 24ZR1423200Guangdong Basic and Applied Basic Research Foundation, China 2026A1515010148National Natural Science Foundation of China 52205114National Natural Science Foundation of China 52375112National Natural Science Foundation of China 52575129National Natural Science Foundation of China 52575130Research Grants Council, University Grants Committee CUHK14211823Shenzhen Natural Science Fund JCYJ20230808105206013
6 · The paper itself

Abstract

Magneto-mechano-electric energy harvesting from stray magnetic fields near power infrastructure is a promising approach for autonomous wireless sensor networks. However, state-of-the-art magneto-mechano-electric energy harvesters (MME-EHs) fail to capture multi-directional 50/60 Hz magnetic fields of power infrastructure due to frequency mismatch and unidirectional responsiveness. To break this bottleneck, this study proposes a gecko-like MME-EH that mimics the flexible, symmetrical movement of gecko limbs to achieve coordinated twisting and bending. The centrally symmetric configuration with low clamping loss allows for high magnetic loads and large beam deformation, resulting in high energy output for driving long-distance wireless sensor systems. Under a weak 60 Hz magnetic field (

Indexed as

energy harvestingLoRa communicationmagneto–mechano–electricmulti‐directionalself‐powered

Identifiers

PMID41903123
PMCPMC13252662

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.