The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Painting a high-output triboelectric nanogenerator on paper for harvesting energy from human body motion
Abstract
Abstract Paper-based triboelectric nanogenerators (TENGs) represent an affordable, green, and eco-friendly energy harvesting methodology. In this work, we propose a novel X-shaped paper TENG (XP-TENG) formed from a ballpoint ink layer coated by painting with a commercial brush pen. The paper and Teflon tape serve as the triboelectric pairs, with the paper serving as the supporting component. Moreover, the XP-TENG is capable of providing two working patterns that can yield an expanded scope of practical applications. A stacked XP-TENG was proposed for increasing the output performance and harvesting the mechanical energy generated by motion of the human body. This staked XP-TENG can directly light up 101 blue high-power LEDs with working voltage of 3.4 V. The fabricated XP-TENG can be used for harvesting mechanical energy from human walking.
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
Ge, X., Gu, C., Wang, X., & Tu, J. (2017) · Journal of Materials Chemistry A · doi:10.1039/c7ta01659j · Cited by 372
Cited by
Zhao, Z., Xia, K., Hou, Y., Zhang, Q., Ye, Z., & Lu, J. (2021) · Chemical Society Reviews · doi:10.1039/d1cs00800e · Cited by 490
Self-citationHassan, M., Abbas, G., Li, N., Afzal, A., Haider, Z., Ahmed, S., Xu, X., Pan, C., & Peng, Z. (2022) · Advanced Materials Technologies · doi:10.1002/admt.202100773 · Cited by 284
Qu, Z., Huang, M., Chen, C., An, Y., Liu, H., Zhang, Q., Wang, X., Liu, Y., Yin, W., & Li, X. (2022) · Advanced Functional Materials · doi:10.1002/adfm.202202048 · Cited by 88
Metadata
- Authors
- Xia, K., Zhu, Z., Zhang, H., Du, C., Xu, Z., & Wang, R.
- Venue
- Nano Energy
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 50
- Pages
- 571-580
- ISSN
- 2211-2855 (ISSN-L)
- OpenAlex
- W2807303100
- Cited by
- 277
- References
- 1
- FWCI
- 8.97
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Painting a high-output triboelectric nanogenerator on paper for harvesting energy from human body motion. https://app.cochat.ai/papers/10.1016/j.nanoen.2018.06.019
- The paper
- Xia, K., Zhu, Z., Zhang, H., Du, C., Xu, Z., & Wang, R. (2018). Painting a high-output triboelectric nanogenerator on paper for harvesting energy from human body motion. Nano Energy. https://doi.org/10.1016/j.nanoen.2018.06.019
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.
