The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Triboelectric tactile sensor for pressure and temperature sensing in high-temperature applications
Open accessAbstract
Skin-like sensors capable of detecting multiple stimuli simultaneously have great potential in cutting-edge human-machine interaction. However, realizing multimodal tactile recognition beyond human tactile perception still faces significant challenges. Here, an extreme environments-adaptive multimodal triboelectric sensor was developed, capable of detecting pressure/temperatures beyond the range of human perception. Based on triboelectric nanogenerator technology, an asymmetric structure capable of independently outputting dual signals was designed to improve perception sensitivity. By converting the signals and the stimuli into feature matrices, parallel perception of complex objects (with a recognition rate of 94%) and temperature at high temperatures was achieved. The proposed multimodal triboelectric tactile sensor represents progress in maximum detection range and rapid response, realizing the upper limit of human skin’s high-temperature sensing (60 °C) with a working temperature of 200 °C. The proposed self-powered multimodal sensing system offers a wider range of possibilities for human/robot/environment interaction applications. Existing tactile sensors struggle with high-temperature environments. Here, authors developed a triboelectric tactile sensor with an asymmetric structure and heat-resistant materials, enabling 94% object recognition rate, fast response times, and stable performance up to 200 °C.
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
Self-powered soft robot in the Mariana Trench
Li, G., Chen, X., Zhou, F., Liang, Y., Xiao, Y., Cao, X., Zhang, Z., Zhang, M., Wu, B., Yin, S., et al. (2021) · Nature · doi:10.1038/s41586-020-03153-z · Cited by 1,198
Keeping cool: Enhanced optical reflection and radiative heat dissipation in Saharan silver ants
Shi, N. N., Tsai, C.-C., Camino, F., Bernard, G. D., Yu, N., & Wehner, R. (2015) · Science · doi:10.1126/science.aab3564 · Cited by 783
Zhang, F., Zang, Y., Huang, D., Di, C.-A., & Zhu, D. (2015) · Nature Communications · doi:10.1038/ncomms9356 · Cited by 668
A bioinspired multilegged soft millirobot that functions in both dry and wet conditions
Lu, H., Zhang, M., Yang, Y., Huang, Q., Fukuda, T., Wang, Z., & Shen, Y. (2018) · Nature Communications · doi:10.1038/s41467-018-06491-9 · Cited by 569
Piezo1 Channels Are Inherently Mechanosensitive
Syeda, R., Florendo, M. N., Cox, C. D., Kefauver, J. M., Santos, J. S., Martinac, B., & Patapoutian, A. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.10.033 · Cited by 532
Sun, Z., Zhu, M., Shan, X., & Lee, C. (2022) · Nature Communications · doi:10.1038/s41467-022-32745-8 · Cited by 532
Wen, F., Zhang, Z., He, T., & Lee, C. (2021) · Nature Communications · doi:10.1038/s41467-021-25637-w · Cited by 494
Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition
Li, G., Liu, S., Wang, L., & Zhu, R. (2020) · Science Robotics · doi:10.1126/scirobotics.abc8134 · Cited by 477
A Flexible Bimodal Sensor Array for Simultaneous Sensing of Pressure and Temperature
Tien, N. T., Jeon, S., Kim, D., Trung, T. Q., Jang, M., Hwang, B., Byun, K., Bae, J., Lee, E., Tok, J. B. ‐., et al. (2014) · Advanced Materials · doi:10.1002/adma.201302869 · Cited by 438
An, B. W., Heo, S., Ji, S., Bien, F., & Park, J.-U. (2018) · Nature Communications · doi:10.1038/s41467-018-04906-1 · Cited by 426
Metadata
- Authors
- Liu, Y., Wang, J., Liu, T., Wei, Z., Luo, B., Chi, M., Zhang, S., Cai, C., Gao, C., Zhao, T., Wang, S., & Nie, S.
- Venue
- Nature Communications
- Published
- 2025-01-03
- Volume
- 16
- Issue
- 1
- Pages
- 383-383
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W4406028065
- Cited by
- 291
- References
- 53
- FWCI
- 69.00
- 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: Triboelectric tactile sensor for pressure and temperature sensing in high-temperature applications. https://app.cochat.ai/papers/10.1038/s41467-024-55771-0
- The paper
- Liu, Y., Wang, J., Liu, T., Wei, Z., Luo, B., Chi, M., Zhang, S., Cai, C., Gao, C., Zhao, T., Wang, S., & Nie, S. (2025). Triboelectric tactile sensor for pressure and temperature sensing in high-temperature applications. Nature Communications. https://doi.org/10.1038/s41467-024-55771-0
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.