The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.
Material choices for triboelectric nanogenerators: A critical review
Open accessAbstract
A triboelectric nanogenerator (TENG) is a novel technology with applications in many areas, including energy harvesting, self‐powered sensing, medication, and electronics. The materials used as triboelectric layers are diverse and include polymers, metals, and inorganic materials. The most commonly used materials are dielectric polymers such as PTFE, FEP, PDMS, and Kapton. Green materials, such as cellulose‐based materials, have recently gained increasing interest, and the performance of TENGs using cellulose materials has improved. The material choices are of great importance for TENGs since the triboelectric effects of the materials are fundamental for TENGs. To design a TENG for a particular application, several parameters need to be considered, such as power density, stability, flexibility, and sustainability. This critical review will summarize and evaluate the material choices for TENGs in different applications. image
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Flexible triboelectric generator
Fan, F.-R., Tian, Z.-Q., & Lin Wang, Z. (2012) · Nano Energy · doi:10.1016/j.nanoen.2012.01.004 · Cited by 6,705
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
Quantifying the triboelectric series
Zou, H., Zhang, Y., Guo, L., Wang, P., He, X., Dai, G., Zheng, H., Chen, C., Wang, A. C., Xu, C., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09461-x · Cited by 1,920
Wang, Z. L. (2014) · Faraday Discuss. · doi:10.1039/c4fd00159a · Cited by 1,749
Reviving Vibration Energy Harvesting and Self-Powered Sensing by a Triboelectric Nanogenerator
Chen, J., & Wang, Z. L. (2017) · Joule · doi:10.1016/j.joule.2017.09.004 · Cited by 1,021
Wang, S., Xie, Y., Niu, S., Lin, L., & Wang, Z. L. (2014) · Advanced Materials · doi:10.1002/adma.201305303 · Cited by 1,001
Standards and figure-of-merits for quantifying the performance of triboelectric nanogenerators
Zi, Y., Niu, S., Wang, J., Wen, Z., Tang, W., & Wang, Z. L. (2015) · Nature Communications · doi:10.1038/ncomms9376 · Cited by 897
Radial-arrayed rotary electrification for high performance triboelectric generator
Zhu, G., Chen, J., Zhang, T., Jing, Q., & Wang, Z. L. (2014) · Nature Communications · doi:10.1038/ncomms4426 · Cited by 868
Wen, Z., Yeh, M.-H., Guo, H., Wang, J., Zi, Y., Xu, W., Deng, J., Zhu, L., Wang, X., Hu, C., et al. (2016) · Science Advances · doi:10.1126/sciadv.1600097 · Cited by 854
Zi, Y., Guo, H., Wen, Z., Yeh, M.-H., Hu, C., & Wang, Z. L. (2016) · ACS Nano · doi:10.1021/acsnano.6b01569 · Cited by 827
Cited by
End-to-end design of wearable sensors
Ates, H. C., Nguyen, P. Q., Gonzalez-Macia, L., Morales-Narváez, E., Güder, F., Collins, J. J., & Dincer, C. (2022) · Nature Reviews Materials · doi:10.1038/s41578-022-00460-x · Cited by 1,306
Metadata
- Authors
- Zhang, R., & Olin, H.
- Venue
- EcoMat
- Publisher
- Wiley
- Published
- 2020-10-27
- Volume
- 2
- Issue
- 4
- ISSN
- 2567-3173 (ISSN-L)
- OpenAlex
- W3096590083
- Cited by
- 533
- References
- 135
- FWCI
- 13.71
- Type
- journal article
- Language
- en
- Open access
- gold
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