Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring
Abstract In-flight icing is a common hazard in unmanned aerial vehicles (UAVs), accounting for 25% of drone accidents due to their sensitivity to weight increase. Anti-icing technology for UAVs remains challenging because of their limited payload capacity and insufficient power to support electrothe...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | npj Flexible Electronics |
| Online Access: | https://doi.org/10.1038/s41528-025-00434-3 |
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| _version_ | 1849389142829432832 |
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| author | Sijia Xu Ruiqi Li Shu Tian Junyu Yu Chengtao An Kai Yang Jing Yang Lei Zhang |
| author_facet | Sijia Xu Ruiqi Li Shu Tian Junyu Yu Chengtao An Kai Yang Jing Yang Lei Zhang |
| author_sort | Sijia Xu |
| collection | DOAJ |
| description | Abstract In-flight icing is a common hazard in unmanned aerial vehicles (UAVs), accounting for 25% of drone accidents due to their sensitivity to weight increase. Anti-icing technology for UAVs remains challenging because of their limited payload capacity and insufficient power to support electrothermal deicing systems. In this study, a self-healing intelligent skin was developed for small-size smart devices, such as UAVs. It provides anti-icing and icephobic capabilities in addition to real-time monitoring of in-flight icing. This skin consists of five layers, including self-healing supramolecular elastomers and electrodes, with an encapsulation layer composed of a specially designed fluoropolymer to decrease the ice nucleation temperature (−28.4 °C) and ice adhesion strength (33.0 kPa). Notably, this skin can monitor ice accretion on the UAV surface in real time, and its sensing performance undergoes complete self-recovery after damage. This study paves the way for intelligent UAVs to operate safely under extreme weather conditions. |
| format | Article |
| id | doaj-art-c5cb68ce8fbd45d5a3db0f9ca27ccb7a |
| institution | Kabale University |
| issn | 2397-4621 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Flexible Electronics |
| spelling | doaj-art-c5cb68ce8fbd45d5a3db0f9ca27ccb7a2025-08-20T03:42:02ZengNature Portfolionpj Flexible Electronics2397-46212025-07-01911910.1038/s41528-025-00434-3Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoringSijia Xu0Ruiqi Li1Shu Tian2Junyu Yu3Chengtao An4Kai Yang5Jing Yang6Lei Zhang7School of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversitySchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversityHaihe laboratory of Sustainable Chemical TransformationsSchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversitySchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversitySchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversitySchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversitySchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin University; Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), Tianjin UniversityAbstract In-flight icing is a common hazard in unmanned aerial vehicles (UAVs), accounting for 25% of drone accidents due to their sensitivity to weight increase. Anti-icing technology for UAVs remains challenging because of their limited payload capacity and insufficient power to support electrothermal deicing systems. In this study, a self-healing intelligent skin was developed for small-size smart devices, such as UAVs. It provides anti-icing and icephobic capabilities in addition to real-time monitoring of in-flight icing. This skin consists of five layers, including self-healing supramolecular elastomers and electrodes, with an encapsulation layer composed of a specially designed fluoropolymer to decrease the ice nucleation temperature (−28.4 °C) and ice adhesion strength (33.0 kPa). Notably, this skin can monitor ice accretion on the UAV surface in real time, and its sensing performance undergoes complete self-recovery after damage. This study paves the way for intelligent UAVs to operate safely under extreme weather conditions.https://doi.org/10.1038/s41528-025-00434-3 |
| spellingShingle | Sijia Xu Ruiqi Li Shu Tian Junyu Yu Chengtao An Kai Yang Jing Yang Lei Zhang Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring npj Flexible Electronics |
| title | Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| title_full | Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| title_fullStr | Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| title_full_unstemmed | Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| title_short | Self-healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| title_sort | self healing unmanned aerial vehicle skin for icing prevention and intelligent monitoring |
| url | https://doi.org/10.1038/s41528-025-00434-3 |
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