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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications
Open accessAbstract
Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade.
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Metadata
- Authors
- Choi, D., Lee, Y., Lin, Z.-H., Cho, S., Kim, M., Ao, C. K., Soh, S., Sohn, C., Jeong, C. K., Lee, J., Lee, M., Lee, S., Ryu, J., Parashar, P., Cho, Y., Ahn, J., Kim, I.-D., Jiang, F., Lee, P. S., Khandelwal, G., Kim, S.-J., Kim, H. S., Song, H.-C., Kim, M., Nah, J., Kim, W., Menge, H. G., Park, Y. T., Xu, W., Hao, J., Park, H., Lee, J.-H., Lee, D.-M., Kim, S.-W., Park, J. Y., Zhang, H., Zi, Y., Guo, R., Cheng, J., Yang, Z., Xie, Y., Lee, S., Chung, J., Oh, I.-K., Kim, J.-S., Cheng, T., Gao, Q., Cheng, G., Gu, G., Shim, M., Jung, J., Yun, C., Zhang, C., Liu, G., Chen, Y., Kim, S., Chen, X., Hu, J., Pu, X., Guo, Z. H., Wang, X., Chen, J., Xiao, X., Xie, X., Jarin, M., Zhang, H., Lai, Y.-C., He, T., Kim, H., Park, I., Ahn, J., Huynh, N. D., Yang, Y., Wang, Z. L., Baik, J. M., & Choi, D.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2023-05-23
- Volume
- 17
- Issue
- 12
- Pages
- 11087-11219
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W4377565774
- Cited by
- 656
- References
- 692
- FWCI
- 48.12
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
