The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Rich lamellar crystal baklava-structured PZT/PVDF piezoelectric sensor toward individual table tennis training
Abstract
Abstract Real-time monitoring of interaction between ball and racket can provide the extremely important information for high quality guidance of individual table tennis training. However, the existing visual monitoring system is hard to reflect the specific interaction force and accurate hit position. Here, we design a self-powered rich lamellar crystal baklava-structured PZT/PVDF piezoelectric sensor for real-time monitoring of table tennis training and the scalable sports. This unique baklava-structured piezocomposite could be massively manufactured by a facile two step method of nonsolvent induced phase separation and hot-press process. As a result, the as-developed sensor exhibits preeminent sensitivity (6.38 mV/N) and ultrafast response time (21 ms). On this basis, we made a smart table tennis racket embedded with 6 × 6 units, which could real-timely fetch the hit location and contact force, then it could provide evaluation and individual guidance for the athletes training. Admittedly, this work not only opens a new way for real-time monitoring of impact location and force in table tennis training beyond current visual detection system, but also paves a new prospect for artificial intelligence electronics toward smart sports.
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
Machine learning: Trends, perspectives, and prospects
Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955
Electroactive phases of poly(vinylidene fluoride): Determination, processing and applications
Martins, P., Lopes, A. C., & Lanceros-Mendez, S. (2014) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2013.07.006 · Cited by 3,494
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
A wearable and highly sensitive pressure sensor with ultrathin gold nanowires
Gong, S., Schwalb, W., Wang, Y., Chen, Y., Tang, Y., Si, J., Shirinzadeh, B., & Cheng, W. (2014) · Nature Communications · doi:10.1038/ncomms4132 · Cited by 2,064
Flexible Nanogenerators for Energy Harvesting and Self‐Powered Electronics
Fan, F. R., Tang, W., & Wang, Z. L. (2016) · Advanced Materials · doi:10.1002/adma.201504299 · Cited by 1,918
Prateek, Thakur, V. K., & Gupta, R. K. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00495 · Cited by 1,659
Conductive Fiber‐Based Ultrasensitive Textile Pressure Sensor for Wearable Electronics
Lee, J., Kwon, H., Seo, J., Shin, S., Koo, J. H., Pang, C., Son, S., Kim, J. H., Jang, Y. H., Kim, D. E., et al. (2015) · Advanced Materials · doi:10.1002/adma.201500009 · Cited by 1,152
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
Dagdeviren, C., Su, Y., Joe, P., Yona, R., Liu, Y., Kim, Y.-S., Huang, Y., Damadoran, A. R., Xia, J., Martin, L. W., et al. (2014) · Nature Communications · doi:10.1038/ncomms5496 · Cited by 987
Ma, Y., Liu, N., Li, L., Hu, X., Zou, Z., Wang, J., Luo, S., & Gao, Y. (2017) · Nature Communications · doi:10.1038/s41467-017-01136-9 · Cited by 788
Self-citation
Cited by
Yang, Y., Pan, H., Xie, G., Jiang, Y., Chen, C., Su, Y., Wang, Y., & Tai, H. (2020) · Sensors and Actuators A: Physical · doi:10.1016/j.sna.2019.111789 · Cited by 496
Yu, J., Xian, S., Zhang, Z., Hou, X., He, J., Mu, J., Geng, W., Qiao, X., Zhang, L., & Chou, X. (2023) · Nano Research · doi:10.1007/s12274-022-5084-x · Cited by 143
Fiber/Yarn and Textile-Based Piezoresistive Pressure Sensors
Yang, Y., Liu, Y., & Yin, R. (2025) · Advanced Fiber Materials · doi:10.1007/s42765-024-00479-5 · Cited by 110
Nie, K., Zhang, X., Hu, Z., Zhang, X., Wang, L., Mei, L., & Wang, H. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.161038 · Cited by 14
Metadata
- Authors
- Tian, G., Deng, W., Gao, Y., Xiong, D., Yan, C., He, X., Yang, T., Jin, L., Chu, X., Zhang, H., Yan, W., & Yang, W.
- Venue
- Nano Energy
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 59
- Pages
- 574-581
- ISSN
- 2211-2855 (ISSN-L)
- OpenAlex
- W2922176345
- Cited by
- 359
- References
- 53
- FWCI
- 11.61
- 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: Rich lamellar crystal baklava-structured PZT/PVDF piezoelectric sensor toward individual table tennis training. https://app.cochat.ai/papers/10.1016/j.nanoen.2019.03.013
- The paper
- Tian, G., Deng, W., Gao, Y., Xiong, D., Yan, C., He, X., Yang, T., Jin, L., Chu, X., Zhang, H., Yan, W., & Yang, W. (2019). Rich lamellar crystal baklava-structured PZT/PVDF piezoelectric sensor toward individual table tennis training. Nano Energy. https://doi.org/10.1016/j.nanoen.2019.03.013
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.
