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Triboelectric nanogenerators as new energy technology and self-powered sensors – Principles, problems and perspectives
Abstract
Triboelectrification is one of the most common effects in our daily life, but it is usually taken as a negative effect with very limited positive applications. Here, we invented a triboelectric nanogenerator (TENG) based on organic materials that is used to convert mechanical energy into electricity. The TENG is based on the conjunction of triboelectrification and electrostatic induction, and it utilizes the most common materials available in our daily life, such as papers, fabrics, PTFE, PDMS, Al, PVC etc. In this short review, we first introduce the four most fundamental modes of TENG, based on which a range of applications have been demonstrated. The area power density reaches 1200 W m −2 , volume density reaches 490 kW m −3 , and an energy conversion efficiency of ∼50–85% has been demonstrated. The TENG can be applied to harvest all kinds of mechanical energy that is available in our daily life, such as human motion, walking, vibration, mechanical triggering, rotation energy, wind, a moving automobile, flowing water, rain drops, tide and ocean waves. Therefore, it is a new paradigm for energy harvesting. Furthermore, TENG can be a sensor that directly converts a mechanical triggering into a self-generated electric signal for detection of motion, vibration, mechanical stimuli, physical touching, and biological movement. After a summary of TENG for micro-scale energy harvesting, mega-scale energy harvesting, and self-powered systems, we will present a set of questions that need to be discussed and explored for applications of the TENG. Lastly, since the energy conversion efficiencies for each mode can be different although the materials are the same, depending on the triggering conditions and design geometry. But one common factor that determines the performance of all the TENGs is the charge density on the two surfaces, the saturation value of which may independent of the triggering configurations of the TENG. Therefore, the triboelectric charge density or the relative charge density in reference to a standard material (such as polytetrafluoroethylene (PTFE)) can be taken as a measuring matrix for characterizing the performance of the material for the TENG.
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“The TENGs can be categorized into four fundamental working modes: [64,71] 1) vertical contact-separation mode, [72][73][74][75][76][77][78] 2) lateral-sliding mode, [79][80][81][82][83] 3) single-electrode mode, [84][85][86][87][88] and 4) freestanding triboelectric-layer mode [89,90]”
From Advances in Blue Energy Fuels: Harvesting Energy from Ocean for Self‐Powered Electrolysis (2025) · cites this paper as [64]
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Li, X., Cao, Y., Yu, X., Xu, Y., Yang, Y., Liu, S., Cheng, T., & Wang, Z. L. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.117977 · Cited by 261
Self-citationLiang, X. D., Jiang, T., Liu, G., Xiao, T., Xu, L., Li, W., Xi, F., Zhang, C., & Wang, Z. L. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201807241 · Cited by 259
Self-citationAhmed, A., Saadatnia, Z., Hassan, I., Zi, Y., Xi, Y., He, X. C., Zu, J. W.-Z., & Wang, Z. L. (2016) · Advanced Energy Materials · doi:10.1002/aenm.201601705 · Cited by 258
Self-citationXu, M., Zhao, T., Wang, C., Zhang, S. L., Li, Z., Pan, X., & Wang, Z. L. (2019) · ACS Nano · doi:10.1021/acsnano.8b08274 · Cited by 258
Self-citationTouchless interactive teaching of soft robots through flexible bimodal sensory interfaces
Liu, W., Duo, Y., Liu, J., Yuan, F., Li, L., Li, L., Wang, G., Chen, B., Wang, S., Yang, H. Q., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32702-5 · Cited by 256
Dong, K., Peng, X., Cheng, R., Ning, C., Jiang, Y., Zhang, Y., & Wang, Z. L. (2022) · Advanced Materials · doi:10.1002/adma.202109355 · Cited by 253
Self-citation
Metadata
- Authors
- Wang, Z. L.
- Affiliations
- Georgia Institute of Technology (US)
- Corresponding author
- Wang, Zhong Lin
- ORCID
- Wang, Zhong Lin
- Venue
- Faraday Discuss.
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2014
- Volume
- 176
- Pages
- 447-458
- ISSN
- 1359-6640 (ISSN-L)
- 1364-5498
- OpenAlex
- W2093018115
- Cited by
- 1,749
- References
- 58
- Citations by year
- 2026: 129 · 2025: 184 · 2024: 176 · 2023: 209 · 2022: 204 · 2021: 206 · 2020: 176 · 2019: 149 · 2018: 139 · 2017: 81 · 2016: 60 · 2015: 33 · 2014: 2
- FWCI
- 30.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Faraday Discussions (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Physical Sciences › Engineering › Mechanical Engineering › Innovative Energy Harvesting Technologies
- Physical Sciences › Engineering › Mechanics of Materials › Tribology and Wear Analysis
- Keywords
- triboelectric nanogenerator, triboelectric energy harvesting, self-powered sensors, mechanical-to-electrical energy conversion, triboelectric charging, electrostatic induction, organic materials, charge density, vibration energy harvesting, human motion energy harvesting, energy conversion efficiency
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