journal article·2025-10-01

Scalable-Manufacturing Triboelectric Fabric Sensor for Pressure Distribution Mapping during Human Body Activities

Qingyun Tao, Cong Zheng, Ruihua Wang, Jiyong Hu, Jinhua Jiang

ACS Applied Materials & Interfaces· Volume 17· Issue 39
Publisher page

Abstract

The scalable manufacturing of all-textile triboelectric pressure sensors capable of high-sensitivity and crosstalk-free pressure distribution mapping remains challenging. This study develops a scalable triboelectric fabric pressure mapping sensor with high sensitivity and free crosstalk by directly interlacing polytetrafluoroethylene/stainless steel (PTFE-SS) braided yarns (negative materials) and the polyamide 66/stainless steel (PA66-SS) braided yarn (positive materials) into the plain derivative weave fabric on an industrialized loom, enabling scalable production. Crucially, the results demonstrate that reducing warp/weft densities significantly boosts electrical output. We further establish the first equivalent circuit model (FO-ECM) for the triboelectric woven fabric pressure mapping sensor, achieving a 0.978 fitting coefficient to predict output under varying weave densities, thereby enabling digital parametric design. Significantly, parameter optimization of warp/weft densities identified an optimal configuration that enhances electrical output, achieving high sensitivity (2.942 V·kPa –1, 0–1 kPa). Furthermore, the triboelectric woven fabric pressure sensor was extended to develop an interference-free triboelectric fabric sensor array (TFSA) through structural spacing design, eliminating crosstalk by elucidating the dominant role of fringe electric fields and quantitatively modeling their spatial decay, thereby enabling high-spatial-resolution pressure mapping. Finally, the distributed pressure mapping of typical human body activities demonstrated the practical performance of the developed triboelectric fabric sensor. This facile integrated approach─from scalable fabrication to interference-free arrays─advances real-time wearable self-powered health monitoring.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Tactile and Sensory Interactions · Muscle activation and electromyography studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Textile Science & Technology, Ministry of Education

Donghua University

Key Laboratory of High-Performance Fibers & Products, Ministry of Education

College of Textiles

Funding

Fundamental Research Funds for the Central Universities

References (47)

Show source-provided references
1. 10.1007/s11432-023-3801-110.1007/s11432-023-3801-1 ↗
2. 10.1016/j.apmt.2022.10169510.1016/j.apmt.2022.101695 ↗
3. 10.1016/j.apmt.2023.10189410.1016/j.apmt.2023.101894 ↗
4. 10.1007/s40820-020-00498-y10.1007/s40820-020-00498-y ↗
5. 10.1007/s42114-022-00525-z10.1007/s42114-022-00525-z ↗
6. 10.1002/adfm.20180878610.1002/adfm.201808786 ↗
7. 10.1002/adma.20150423910.1002/adma.201504239 ↗
8. 10.1016/j.nanoen.2023.10873010.1016/j.nanoen.2023.108730 ↗
9. 10.3390/s1711258510.3390/s17112585 ↗
10. 10.1021/acsami.5b0489210.1021/acsami.5b04892 ↗
11. 10.1039/C7RA02215H10.1039/C7RA02215H ↗
12. 10.1002/adma.20157018510.1002/adma.201570185 ↗
13. 10.1016/j.sna.2018.07.05710.1016/j.sna.2018.07.057 ↗
14. 10.1016/j.cej.2025.16393210.1016/j.cej.2025.163932 ↗
15. 10.1016/j.heliyon.2024.e3084510.1016/j.heliyon.2024.e30845 ↗
16. 10.1021/acsami.1c0281510.1021/acsami.1c02815 ↗
17. 10.1039/D0TA02221G10.1039/D0TA02221G ↗
18. 10.1016/j.nanoen.2022.10745410.1016/j.nanoen.2022.107454 ↗
19. 10.1016/j.nanoen.2024.11062210.1016/j.nanoen.2024.110622 ↗
20. 10.1016/j.nanoen.2025.11072910.1016/j.nanoen.2025.110729 ↗
21. 10.1016/j.mattod.2019.10.02510.1016/j.mattod.2019.10.025 ↗
22. 10.1002/adfm.20230356210.1002/adfm.202303562 ↗
23. 10.1016/j.nanoen.2020.10452810.1016/j.nanoen.2020.104528 ↗
24. 10.1007/s10854-025-14228-w10.1007/s10854-025-14228-w ↗
25. 10.1002/adma.20210935510.1002/adma.202109355 ↗
26. 10.1002/aenm.20220128810.1002/aenm.202201288 ↗
27. 10.1016/j.cej.2024.15887110.1016/j.cej.2024.158871 ↗
28. 10.1016/j.mattod.2021.05.01710.1016/j.mattod.2021.05.017 ↗
29. 10.1016/j.nanoen.2022.10745410.1016/j.nanoen.2022.107454 ↗
30. 10.1016/j.compositesb.2020.10824410.1016/j.compositesb.2020.108244 ↗
31. 10.1002/adma.20170264810.1002/adma.201702648 ↗
32. 10.1016/j.cej.2022.13749110.1016/j.cej.2022.137491 ↗
33. 10.1016/j.nanoen.2021.10658210.1016/j.nanoen.2021.106582 ↗
34. 10.1021/acsami.1c0098310.1021/acsami.1c00983 ↗
35. 10.1002/adfm.20200667910.1002/adfm.202006679 ↗
36. 10.1021/acsnano.0c0052410.1021/acsnano.0c00524 ↗
37. 10.1016/j.nanoen.2022.10776910.1016/j.nanoen.2022.107769 ↗
38. 10.1016/j.cej.2024.15435810.1016/j.cej.2024.154358 ↗
39. 10.1002/admt.20220211610.1002/admt.202202116 ↗
40. 10.1016/j.nanoen.2021.10633510.1016/j.nanoen.2021.106335 ↗
41. 10.1016/j.nanoen.2023.10900810.1016/j.nanoen.2023.109008 ↗
42. 10.1016/j.matt.2023.10.02410.1016/j.matt.2023.10.024 ↗
43. 10.1007/s12274-024-6410-210.1007/s12274-024-6410-2 ↗
44. 10.1002/adma.20150340710.1002/adma.201503407 ↗
45. 10.1021/nn403838y10.1021/nn403838y ↗
46. 10.1021/nn500695q10.1021/nn500695q ↗
47. 10.1002/adfm.20140270310.1002/adfm.201402703 ↗