Self-Powered Sensor for Quantifying Ocean Surface Water Waves Based on Triboelectric Nanogenerator

TLDR

Ocean waves carry valuable marine information, yet high‑precision quantification remains challenging for ocean development and utilization. The authors present a self‑powered, high‑performance triboelectric ocean‑wave spectrum sensor (TOSS) intended to measure surface waves from any direction. TOSS is built with a tubular triboelectric nanogenerator and a hollow‑ball buoy, which removes seawater interference and enables directional measurement. The sensor delivers an ultrahigh sensitivity of 2530 mV mm⁻¹—100× that of previous work—and a 0.1 % error in wave height and period, while extracting six basic wave parameters, velocity and wavelength spectra, and mechanical energy spectrum from its electrical output to support accurate ocean‑big‑data cloud computing.

Abstract

An ocean wave contains various marine information, but it is generally difficult to obtain the high-precision quantification to meet the needs of ocean development and utilization. Here, we report a self-powered and high-performance triboelectric ocean-wave spectrum sensor (TOSS) fabricated using a tubular triboelectric nanogenerator (TENG) and hollow ball buoy, which not only can adapt to the measurement of ocean surface water waves in any direction but also can eliminate the influence of seawater on the performance of the sensor. Based on the high-sensitivity advantage of TENG, an ultrahigh sensitivity of 2530 mV mm-1 (which is 100 times higher than that of previous work) and a minimal monitoring error of 0.1% are achieved in monitoring wave height and wave period, respectively. Importantly, six basic ocean-wave parameters (wave height, wave period, wave frequency, wave velocity, wavelength, and wave steepness), wave velocity spectrum, and mechanical energy spectrum have been derived by the electrical signals of TOSS. Our finding not only can provide ocean-wave parameters but also can offer significant and accurate data support for cloud computing of ocean big data.