The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Self-Healable, Stretchable, Transparent Triboelectric Nanogenerators as Soft Power Sources
Abstract
Despite the rapid advancements of soft electronics, developing compatible energy devices will be the next challenge for their viable applications. Here, we report an energy-harnessing triboelectric nanogenerator (TENG) as a soft electrical power source, which is simultaneously self-healable, stretchable, and transparent. The nanogenerator features a thin-film configuration with buckled Ag nanowires/poly(3,4-ethylenedioxythiophene) composite electrode sandwiched in room-temperature self-healable poly(dimethylsiloxane) (PDMS) elastomers. Dynamic imine bonds are introduced in PDMS networks for repairing mechanical damages (94% efficiency), while the mechanical recovery of the elastomer is imparted to the buckled electrode for electrical healing. By adjusting the buckling wavelength of the electrode, the stretchability and transparency of the soft TENG can be tuned. A TENG (∼50% stretchabitliy, ∼73% transmittance) can recover the electricity genearation (100% healing efficiency) even after accidental cutting. Finally, the conversion of biomechanical energies into electricity (∼100 V, 327 mW/m 2 ) is demonstrated by a skin-like soft TENG. Considering all these merits, this work suggests a potentially promising approach for next-generation soft power sources.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836
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-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-citation
Cited by
Bio-Integrated Wearable Systems: A Comprehensive Review
Ray, T. R., Choi, J., Bandodkar, A. J., Krishnan, S., Gutruf, P., Tian, L., Ghaffari, R., & Rogers, J. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00573 · Cited by 1,350
Smart Textiles for Electricity Generation
Chen, G., Li, Y., Bick, M., & Chen, J. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00821 · Cited by 931
Muscle-Inspired Self-Healing Hydrogels for Strain and Temperature Sensor
Ge, G., Lu, Y., Qu, X., Zhao, W., Ren, Y., Wang, W., Wang, Q., Huang, W., & Dong, X. (2020) · ACS Nano · doi:10.1021/acsnano.9b07874 · Cited by 732
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-citationParida, K., Thangavel, G., Cai, G., Zhou, X., Park, S., Xiong, J., & Lee, P. S. (2019) · Nature Communications · doi:10.1038/s41467-019-10061-y · Cited by 426
Metadata
- Authors
- Sun, J., Pu, X., Liu, M., Yu, A., Du, C., Zhai, J., Hu, W., & Wang, Z. L.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-05-31
- Volume
- 12
- Issue
- 6
- Pages
- 6147-6155
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2806901038
- Cited by
- 332
- References
- 3
- FWCI
- 13.97
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
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.