The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Self-Powered Sensor for Quantifying Ocean Surface Water Waves Based on Triboelectric Nanogenerator
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.
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Citations
Cites
Catch wave power in floating nets
Wang, Z. L. (2017) · Nature · doi:10.1038/542159a · Cited by 708
Self-citationSustainably powering wearable electronics solely by biomechanical energy
Wang, J., Li, S., Yi, F., Zi, Y., Lin, J., Wang, X., Xu, Y., & Wang, Z. L. (2016) · Nature Communications · doi:10.1038/ncomms12744 · Cited by 648
Self-citationTriboelectric nanogenerators for sensitive nano-coulomb molecular mass spectrometry
Li, A., Zi, Y., Guo, H., Wang, Z. L., & Fernández, F. M. (2017) · Nature Nanotechnology · doi:10.1038/nnano.2017.17 · Cited by 324
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Cited by
Choi, D., Lee, Y., Lin, Z.-H., Cho, S., Kim, M., Ao, C. K., Soh, S., Sohn, C., Jeong, C. K., Lee, J., et al. (2023) · ACS Nano · doi:10.1021/acsnano.2c12458 · Cited by 656
Self-citationCao, X., Xiong, Y., Sun, J., Xie, X., Sun, Q., & Wang, Z. L. (2023) · Nano-Micro Letters · doi:10.1007/s40820-022-00981-8 · Cited by 361
Self-citationPang, Y., He, T., Liu, S., Zhu, X., & Lee, C. (2024) · Advanced Science · doi:10.1002/advs.202306574 · Cited by 60
Metadata
- Authors
- Zhang, C., Liu, L., Zhou, L., Yin, X., Wei, X., Hu, Y., Liu, Y., Chen, S., Wang, J., & Wang, Z. L.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-06-05
- Volume
- 14
- Issue
- 6
- Pages
- 7092-7100
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W3033060624
- Cited by
- 167
- References
- 3
- FWCI
- 7.30
- Type
- journal article
- Language
- en
- Open access
- closed
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