Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm
| Autor: | Jianye Li, Hao Wang, Yibing Luo, Zijing Zhou, He Zhang, Huizhi Chen, Kai Tao, Chuan Liu, Lingxing Zeng, Fengwei Huo, Jin Wu |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Nano-Micro Letters, Vol 16, Iss 1, Pp 1-22 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2311-6706 2150-5551 |
| DOI: | 10.1007/s40820-024-01466-6 |
| Popis: | Highlights A novel organohydrogel-based multimodal e-skin with excellent sensing performance for temperature, humidity, pressure, proximity, and NO2 is proposed for the first time, showing powerful sensing capabilities beyond natural skin. The developed multimodal e-skin exhibited extraordinary sensing performance at room temperature, including fast pressure response time (0.2 s), high temperature sensitivity (9.38% °C-1), a wide range of humidity response (22%–98% RH), high NO2 sensitivity (254% ppm-1), a low detection limit (11.1 ppb NO2) and the abilities to sense the proximity of objects accurately, which are yet achieved by previous e-skins. The multimodal e-skin was combined with the deep neural network algorithm and wireless alarm circuit to achieve zero-error classification of different objects and rapid response to NOx leak incidents, proving the feasibility of the e-skin-assisted rescue robot for post-earthquake rescue. |
| Databáze: | Directory of Open Access Journals |
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