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Wave-Adaptive Triboelectric Nanogenerators Highly Compatible With Actual Wave Energy Spectrum for Autonomous Smart Ocean Platform

delete2026-05-18
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PRE
AI
Z
Zhenyuan Dong
N
Ningle Hou
H
Huijing Qiu
X
Xianye Li
王振林 (Zhong Lin Wang)
L
Liang Xu *
DOI:10.1002/aenm.71088delete
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Abstract

Abstract

En 中文
Although triboelectric nanogenerators (TENGs) are regarded as a promising technology for wave energy utilization, most present devices are only effective at relative high frequency with a narrow range, seriously incompatible with actual wave spectrum of energy distribution. Here, we present a wave-adaptive triboelectric nanogenerator based on device-anchor-water synergistic effect, achieving ultrawide frequency range highly compatible with actual wave spectrum via a simple structure. Specifically, the device adopts a novel partial Ferris wheel design, featuring revolution-spin coupling motion of planet TENGs under agitations, and the potential energy landscape of the wheel can be tuned for unique non-linear behavior, which imparts the device supreme adaptation capability to real capricious waves of varying frequencies and amplitudes, maximizing power take-off. Based on the high-performance generator, an autonomous smart ocean platform for customizable marine sensing applications is developed. A prototype for smart marine ranch using the platform can collect and transmit local data automatically to the base station 1.24 km away, surpassing present record and ready for practical application. The work provides not only a general multifunctional architecture for self-powered marine Internet-of-Things, but also a paradigm shift for solving the wave-adaptation and spectrum-matching challenges in wave energy harvesting, greatly enhancing practical performance.
Keywords:
smart ocean
triboelectric nanogenerator
wave adaptive
wave energy harvesting
wave energy spectrum

Journal

Advanced Energy Materials cover
Advanced Energy Materials
IF:
26
Papers:
1.0W
Citations:
15.7W

Organization

C
chinese academy of sciences
Scholars:
55.2W
Papers: 44.6W
Citations: 704