Self‐Sensing Cord‐Rubber Composites Based on Cord/ CNT for In‐Situ Damage Monitoring
Source abstract
Abstract
ABSTRACT In situ monitoring is becoming a technology breakthrough in aviation structural health monitoring, offering significant advancements in system safety and maintenance planning. However, traditional structural health monitoring, involving the permanent integration of sensors into composites, is still quite challenging for cord–rubber flexible structures. This study presents a smart nylon cord (NC) sensor fabricated by dip‐coating carbon nanotubes (CNT) onto a polydopamine‐modified NC (P‐NC) surface. Benefit from the synergistic modification of polydopamine (PDA) and CNTs, the CNT@PDA@NC (CNT/P‐NC) exhibits stable sensing properties (3000 cycles) and mechanical properties (enhanced interface strength of 11.48%). The CNT/P‐NC reinforced nitrile rubber composite (NBR/CNT/P‐NC) exhibits exceptional self‐sensing performance for deformation monitoring under quasi‐static and dynamic mechanical loading. Furthermore, in situ fatigue damage monitoring is realized by the correlation between CNT network conductivity degradation and damage accumulation. The finding shows that the NBR/CNT/P‐NC self‐sensing composites successfully detect internal mechanical information, monitor damage evolution in real‐time (0–250,000 cycles), and provide failure warnings. It has great potential for in situ monitoring of rubber components, including fabric rubber seals on cabin doors.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Smart Materials for Construction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechatronics Engineering Harbin Institute of Technology Harbin China
National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin China
Center for Rubber Composite Materials and Structures Harbin Institute of Technology Weihai China
References (49)
Show source-provided references
1. 10.1016/j.ijfatigue.2025.10881510.1016/j.ijfatigue.2025.108815 ↗
2. 10.1016/j.coco.2024.10221410.1016/j.coco.2024.102214 ↗
3. 10.1016/j.polymer.2023.12625310.1016/j.polymer.2023.126253 ↗
4. 10.1002/app.5594910.1002/app.55949 ↗
5. 10.1016/j.jmps.2024.10574510.1016/j.jmps.2024.105745 ↗
6. 10.1038/s41598‐024‐64233‐y10.1038/s41598‐024‐64233‐y ↗
7. 10.1007/s10118‐023‐2948‐910.1007/s10118‐023‐2948‐9 ↗
8. 10.1016/j.compositesb.2021.10913610.1016/j.compositesb.2021.109136 ↗
9. 10.1016/j.jmrt.2024.07.19610.1016/j.jmrt.2024.07.196 ↗
10. 10.1016/j.measurement.2025.11672910.1016/j.measurement.2025.116729 ↗
11. 10.1088/2631‐7990/ada83710.1088/2631‐7990/ada837 ↗
12. 10.1016/j.compositesb.2021.10916710.1016/j.compositesb.2021.109167 ↗
13. 10.1016/j.tws.2022.11016010.1016/j.tws.2022.110160 ↗
14. 10.1016/j.compscitech.2019.10797610.1016/j.compscitech.2019.107976 ↗
15. 10.1007/s11431‐022‐2261‐110.1007/s11431‐022‐2261‐1 ↗
16. 10.1016/j.engfailanal.2025.10932610.1016/j.engfailanal.2025.109326 ↗
17. 10.1021/acsami.4c0105510.1021/acsami.4c01055 ↗
18. 10.1007/s11431‐023‐2535‐010.1007/s11431‐023‐2535‐0 ↗
19. 10.1016/j.engfailanal.2024.10878610.1016/j.engfailanal.2024.108786 ↗
20. 10.1002/pc.2930010.1002/pc.29300 ↗
21. 10.1109/JSEN.2013.229462610.1109/JSEN.2013.2294626 ↗
22. 10.1016/j.compstruct.2016.06.00710.1016/j.compstruct.2016.06.007 ↗
23. 10.1007/s10853‐022‐08106‐710.1007/s10853‐022‐08106‐7 ↗
24. 10.1016/j.compscitech.2020.10831210.1016/j.compscitech.2020.108312 ↗
25. 10.1016/j.measurement.2021.11057510.1016/j.measurement.2021.110575 ↗
26. 10.1002/pc.2792910.1002/pc.27929 ↗
27. 10.1016/j.matchemphys.2025.13086010.1016/j.matchemphys.2025.130860 ↗
28. 10.1002/pc.2793410.1002/pc.27934 ↗
29. 10.1002/adma.20210730910.1002/adma.202107309 ↗
30. 10.1002/pc.2866410.1002/pc.28664 ↗
31. 10.1016/j.apmt.2024.10230210.1016/j.apmt.2024.102302 ↗
32. 10.1016/j.cej.2024.15438610.1016/j.cej.2024.154386 ↗
33. 10.1016/j.compscitech.2018.07.02310.1016/j.compscitech.2018.07.023 ↗
34. 10.1016/j.engstruct.2024.11804910.1016/j.engstruct.2024.118049 ↗
35. 10.1002/pc.2637510.1002/pc.26375 ↗
36. 10.1016/j.compscitech.2022.10933610.1016/j.compscitech.2022.109336 ↗
37. 10.1002/pc.2751910.1002/pc.27519 ↗
38. 10.1002/elps.20190039210.1002/elps.201900392 ↗
39. 10.1016/j.cej.2022.13971610.1016/j.cej.2022.139716 ↗
40. 10.1021/acsami.8b1882310.1021/acsami.8b18823 ↗
41. 10.1016/j.nanoen.2021.10684010.1016/j.nanoen.2021.106840 ↗
42. 10.1021/acsnano.8b0780510.1021/acsnano.8b07805 ↗
43. 10.1016/j.compscitech.2021.10909010.1016/j.compscitech.2021.109090 ↗
44. 10.1002/pc.2675910.1002/pc.26759 ↗
45. 10.1016/j.surfin.2022.10208610.1016/j.surfin.2022.102086 ↗
46. Hearle J. W. S. · 1971
47. 10.1016/j.compscitech.2018.10.02510.1016/j.compscitech.2018.10.025 ↗
48. 10.1177/0892705721106770310.1177/08927057211067703 ↗
49. 10.1002/mame.20200036110.1002/mame.202000361 ↗