Unifying energy and information harvesting for high-rate self-powered sensing

High-fidelity sensing remains highly challenging in self-powered systems, as the limited power of energy harvesters constrains data acquisition and transmission. In this work, we present a wireless, intelligent, self-powered environmental node (WISE-Node) that simultaneously harvests energy and collects sensing information from ambient vibrations. Its multi-contact triboelectric vibration energy harvester (MC-TVEH) achieves an ultra-wide bandwidth of 10–300 Hz, delivering peak and RMS power densities of 13.42 kW/m 3 and 1.73 kW/m 3 , respectively. The WISE-Node also functions as a broadband sensor, accurately tracking excitation frequencies via FFT analysis ( R 2 = 0.9997 across 3–10,000 Hz). Using a Random Forest classifier on the acquired data, the WISE-Node identifies flange conditions with 99.38% accuracy. Field tests on marine engines and generators validate its robust performance, achieving a cold start in just 28.8 s and maintaining fully self-powered 1000 Hz sampling and stable wireless transmission. These results highlight the proposed WISE-Node’s strong potential for self-sustained high-fidelity sensing, thereby advancing next-generation battery-free industrial IoT and digital twin technologies.

Authors

Institutions

Publication Details

Journal
Science Advances
Published
2026-08-21
DOI
https://doi.org/10.1126/sciadv.aeh0436
Primary Topic
Innovative Energy Harvesting Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unifying energy and information harvesting for high-rate self-powered sensing

Hongyong Yu, Taili Du, Guobiao Hu, Minyi Xu et al.
Science Advances
Innovative Energy Harvesting Technologies
article

Unifying energy and information harvesting for high-rate self-powered sensing

Hongyong Yu, Taili Du, Guobiao Hu, Minyi Xu, Yawei Wang, Ziyue Xi, Hengxu Du, Yaozi Zheng, Jixiang Chen, Yizhou Li, Quanke Su
article en

Abstract

High-fidelity sensing remains highly challenging in self-powered systems, as the limited power of energy harvesters constrains data acquisition and transmission. In this work, we present a wireless, intelligent, self-powered environmental node (WISE-Node) that simultaneously harvests energy and collects sensing information from ambient vibrations. Its multi-contact triboelectric vibration energy harvester (MC-TVEH) achieves an ultra-wide bandwidth of 10–300 Hz, delivering peak and RMS power densities of 13.42 kW/m 3 and 1.73 kW/m 3 , respectively. The WISE-Node also functions as a broadband sensor, accurately tracking excitation frequencies via FFT analysis ( R 2 = 0.9997 across 3–10,000 Hz). Using a Random Forest classifier on the acquired data, the WISE-Node identifies flange conditions with 99.38% accuracy. Field tests on marine engines and generators validate its robust performance, achieving a cold start in just 28.8 s and maintaining fully self-powered 1000 Hz sampling and stable wireless transmission. These results highlight the proposed WISE-Node’s strong potential for self-sustained high-fidelity sensing, thereby advancing next-generation battery-free industrial IoT and digital twin technologies.

Science AdvancesVol. 12(34)
Dalian Maritime University (CN), University of Hong Kong (HK), South China University of Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 19%
Innovative Energy Harvesting Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Unifying energy and information harvesting for high-rate self-powered sensing — Hongyong Yu, Taili Du, et al. · Science Advances (2026) | TGRS Research Map | TGRS