The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Advances in Nanostructures for High‐Performance Triboelectric Nanogenerators
Abstract
With the rapid development of the Internet of Things (IoT) and the ongoing Fourth Industrial Revolution, the effective conversion of wasted ambient mechanical energy from the environment to generate electricity is regarded as one of the most pivotal technologies for powering widely distributed electronics in the era of the Internet of Things. Although the triboelectric nanogenerator (TENG), based on the coupling effect of contact electrification and electrostatic induction, has recently undergone a tremendous evolution with the development of various features such as flexibility, conformability, and user‐friendliness, further improvement of the output performance is still required for usage toward practical applications for the next‐generation of IoT devices. In this review article, surface nanostructure modification methods for high‐performance triboelectric nanogenerators are systematically summarized. The field is deeply reviewed, with the methods classified into four categories: templating method, appending method, etching method, and crumpling method. Finally, an in‐depth discussion of the existing challenges and the direction of future efforts for enhancing TENG output performance are clearly stated, which can contribute to promoting further development of the field.
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Cites
Progress in triboelectric nanogenerators as a new energy technology and self-powered sensors
Wang, Z. L., Chen, J., & Lin, L. (2015) · Energy & Environmental Science · doi:10.1039/c5ee01532d · Cited by 2,174
Self-citationYang, Y., Zhang, H., Lin, Z.-H., Zhou, Y. S., Jing, Q., Su, Y., Yang, J., Chen, J., Hu, C., & Wang, Z. L. (2013) · ACS Nano · doi:10.1021/nn403838y · Cited by 798
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Xu, K., Lu, Y., & Takei, K. (2019) · Advanced Materials Technologies · doi:10.1002/admt.201800628 · Cited by 602
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Silk fabric-based wearable thermoelectric generator for energy harvesting from the human body
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Shi, Q., Zhang, Z., Chen, T., & Lee, C. (2019) · Nano Energy · doi:10.1016/j.nanoen.2019.05.033 · Cited by 202
Smart watch accelerometry for analysis and diagnosis of tremor
Wile, D. J., Ranawaya, R., & Kiss, Z. H. T. (2014) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.04.021 · Cited by 148
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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-citationAmbulatory Cardiovascular Monitoring Via a Machine‐Learning‐Assisted Textile Triboelectric Sensor
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Self-citationFunctional Fiber Materials to Smart Fiber Devices
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Wearable Biosensors for Non-Invasive Sweat Diagnostics
Xu, J., Fang, Y., & Chen, J. (2021) · Biosensors · doi:10.3390/bios11080245 · Cited by 208
Self-citationAdvances in Blue Energy Fuels: Harvesting Energy from Ocean for Self‐Powered Electrolysis
Ock, I. W., Yin, J., Wang, S., Zhao, X., Baik, J. M., & Chen, J. (2025) · Advanced Energy Materials · doi:10.1002/aenm.202400563 · Cited by 64
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Metadata
- Authors
- Zou, Y., Xu, J., Chen, K., & Chen, J.
- Venue
- Advanced Materials Technologies
- Publisher
- Wiley
- Published
- 2021-01-27
- Volume
- 6
- Issue
- 3
- ISSN
- 2365-709X (ISSN-L)
- OpenAlex
- W3126095363
- Cited by
- 220
- References
- 9
- FWCI
- 11.55
- Type
- journal article
- Language
- en
- Open access
- closed
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