The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Engineering Materials at the Nanoscale for Triboelectric Nanogenerators
Open accessAbstract
Taking advantage of the coupling effect of contact electrification and electrostatic induction, triboelectric nanogenerators can effectively convert various forms of ambient mechanical energy into electricity, and therefore have attracted much attention, with broad applications in energy harvesting, active sensing, and biomedical therapy, which are anticipated to be an indispensable component in the era of the Internet of things. To improve the mechanical-to-electrical conversion, various strategies have been reported to engineer the materials used at the nanoscale with physical, chemical, biological, and hybrid approaches. These strategies to enhance the output performance and extend the applications of triboelectric nanogenerators are comprehensively reviewed and summarized in this article. Furthermore, perspectives are also discussed in depth, with an emphasis on future research directions to further advance developments within the field.
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
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-citationBiodegradable triboelectric nanogenerator as a life-time designed implantable power source
Zheng, Q., Zou, Y., Zhang, Y., Liu, Z., Shi, B., Wang, X., Jin, Y., Ouyang, H., Li, Z., & Wang, Z. L. (2016) · Science Advances · doi:10.1126/sciadv.1501478 · Cited by 617
Triboelectric Nanogenerator Enabled Body Sensor Network for Self-Powered Human Heart-Rate Monitoring
Lin, Z., Chen, J., Li, X., Zhou, Z., Meng, K., Wei, W., Yang, J., & Wang, Z. L. (2017) · ACS Nano · doi:10.1021/acsnano.7b02975 · Cited by 494
Self-citationEffective Wound Healing Enabled by Discrete Alternative Electric Fields from Wearable Nanogenerators
Long, Y., Wei, H., Li, J., Yao, G., Yu, B., Ni, D., Gibson, A. L., Lan, X., Jiang, Y., Cai, W., et al. (2018) · ACS Nano · doi:10.1021/acsnano.8b07038 · Cited by 397
Li, S., Fan, Y., Chen, H., Nie, J., Liang, Y., Tao, X., Zhang, J., Chen, X., Fu, E., & Wang, Z. L. (2020) · Energy & Environmental Science · doi:10.1039/c9ee03307f · Cited by 356
Pan, R., Xuan, W., Chen, J., Dong, S., Jin, H., Wang, X., Li, H., & Luo, J. (2018) · Nano Energy · doi:10.1016/j.nanoen.2017.12.048 · Cited by 308
Self-citationWu, C., Kim, T. W., Park, J. H., An, H., Shao, J., Chen, X., & Wang, Z. L. (2017) · ACS Nano · doi:10.1021/acsnano.7b03657 · Cited by 275
Zheng, Y., Cheng, L., Yuan, M., Wang, Z., Zhang, L., Qin, Y., & Jing, T. (2014) · Nanoscale · doi:10.1039/c4nr01934b · Cited by 250
Cited by
Electronic Textiles for Wearable Point-of-Care Systems
Chen, G., Xiao, X., Zhao, X., Tat, T., Bick, M., & Chen, J. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00502 · Cited by 688
Self-citationAmbulatory Cardiovascular Monitoring Via a Machine‐Learning‐Assisted Textile Triboelectric Sensor
Fang, Y., Zou, Y., Xu, J., Chen, G., Zhou, Y., Deng, W., Zhao, X., Roustaei, M., Hsiai, T. K., & Chen, J. (2021) · Advanced Materials · doi:10.1002/adma.202104178 · Cited by 380
Self-citationEmerging Indoor Photovoltaic Technologies for Sustainable Internet of Things
Pecunia, V., Occhipinti, L. G., & Hoye, R. L. Z. (2021) · Advanced Energy Materials · doi:10.1002/aenm.202100698 · Cited by 322
Wearable Biosensors for Non-Invasive Sweat Diagnostics
Xu, J., Fang, Y., & Chen, J. (2021) · Biosensors · doi:10.3390/bios11080245 · Cited by 208
Self-citationPrasad, G., Graham, S. A., Yu, J. S., Kim, H., & Lee, D.-W. (2023) · Nano Energy · doi:10.1016/j.nanoen.2023.108178 · Cited by 114
Metadata
- Authors
- Zhou, Y., Deng, W., Xu, J., & Chen, J.
- Venue
- Cell Reports Physical Science
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 1
- Issue
- 8
- Pages
- 100142
- ISSN
- 2666-3864 (ISSN-L)
- OpenAlex
- W3048899972
- Cited by
- 265
- References
- 8
- FWCI
- 11.50
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Engineering Materials at the Nanoscale for Triboelectric Nanogenerators. https://app.cochat.ai/papers/10.1016/j.xcrp.2020.100142
- The paper
- Zhou, Y., Deng, W., Xu, J., & Chen, J. (2020). Engineering Materials at the Nanoscale for Triboelectric Nanogenerators. Cell Reports Physical Science. https://doi.org/10.1016/j.xcrp.2020.100142
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.
