The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Beyond energy harvesting - multi-functional triboelectric nanosensors on a textile
Abstract
Abstract To accurately evaluate the wellbeing condition of a person, sensing systems with versatile functions are needed. Apart from directly monitoring vital signs, an indirect monitoring approach by measuring human activities with wearable devices has emerged. Herein, a smart textile fabricated with a simple dip coating method is developed with multiple functionalities, such as energy harvesting, physical sensing, and even gas sensing. A maximum output power density of 2 W m−2 is achieved with a layer of PEDOT: PSS coated textile and PTFE under foot stepping at 2 Hz, and the matched impedance is as low as 14 MΩ. A height-varying multi-arch strain sensor with a large strain sensing range from 10% to 160% is developed. Furthermore, the arch-shaped strain sensors mounted on the human fingers are demonstrated to monitor hand gestures for American Sign Language interpretation and robotic hand control. Additionally, four textile-based sensors located at different body parts are employed to track human activities. Beyond that, the smart textile is also demonstrated to be a building block of a wearable CO2 sensor. Looking forward, this smart textile could be incorporated into real clothes as both energy harvesters and various functional self-powered sensors to enable smart clothes for healthcare monitoring applications.
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
Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis
Gao, W., Emaminejad, S., Nyein, H. Y. Y., Challa, S., Chen, K., Peck, A., Fahad, H. M., Ota, H., Shiraki, H., Kiriya, D., et al. (2016) · Nature · doi:10.1038/nature16521 · Cited by 5,087
Hammock, M. L., Chortos, A., Tee, B. C. ‐., Tok, J. B. ‐., & Bao, Z. (2013) · Advanced Materials · doi:10.1002/adma.201302240 · Cited by 2,396
Cai, G., Wang, J., Qian, K., Chen, J., Li, S., & Lee, P. S. (2017) · Advanced Science · doi:10.1002/advs.201600190 · Cited by 921
Liu, Y., Norton, J. J. S., Qazi, R., Zou, Z., Ammann, K. R., Liu, H., Yan, L., Tran, P. L., Jang, K.-I., Lee, J. W., et al. (2016) · Science Advances · doi:10.1126/sciadv.1601185 · Cited by 397
Zhang, S. L., Lai, Y., He, X., Liu, R., Zi, Y., & Wang, Z. L. (2017) · Advanced Functional Materials · doi:10.1002/adfm.201606695 · Cited by 235
Lee, T., Lee, W., Kim, S., Kim, J. J., & Kim, B. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201601237 · Cited by 166
Digitalized self-powered strain gauge for static and dynamic measurement
Su, Z., Wu, H., Chen, H., Guo, H., Cheng, X., Song, Y., Chen, X., & Zhang, H. (2017) · Nano Energy · doi:10.1016/j.nanoen.2017.10.004 · Cited by 37
Cited by
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
Zhu, M., Sun, Z., Zhang, Z., Shi, Q., He, T., Liu, H., Chen, T., & Lee, C. (2020) · Science Advances · doi:10.1126/sciadv.aaz8693 · Cited by 784
Self-citationElectronic 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
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-citationQin, Y., Mo, J., Liu, Y., Zhang, S., Wang, J., Fu, Q., Wang, S., & Nie, S. (2022) · Advanced Functional Materials · doi:10.1002/adfm.202201846 · Cited by 382
Metadata
- Authors
- He, T., Shi, Q., Wang, H., Wen, F., Chen, T., Ouyang, J., & Lee, C.
- Venue
- Nano Energy
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 57
- Pages
- 338-352
- ISSN
- 2211-2855 (ISSN-L)
- OpenAlex
- W2905376763
- Cited by
- 219
- References
- 7
- FWCI
- 10.48
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Beyond energy harvesting - multi-functional triboelectric nanosensors on a textile. https://app.cochat.ai/papers/10.1016/j.nanoen.2018.12.032
- The paper
- He, T., Shi, Q., Wang, H., Wen, F., Chen, T., Ouyang, J., & Lee, C. (2019). Beyond energy harvesting - multi-functional triboelectric nanosensors on a textile. Nano Energy. https://doi.org/10.1016/j.nanoen.2018.12.032
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.