Bioinspired cilia-based electronic skin for multimodal mechanical sensing via additive manufacturing

Jiangnan Yan , Jianing Ding , Yang Cao , Hongyu Yi , Limeng Zhan , Yifan Gao , Kongyu Ge , Hongjun Ji , Mingyu Li , Huanhuan Feng

Soft Science ›› 2025, Vol. 5 ›› Issue (2) : 22

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Soft Science ›› 2025, Vol. 5 ›› Issue (2) :22 DOI: 10.20517/ss.2025.03
Research Article

Bioinspired cilia-based electronic skin for multimodal mechanical sensing via additive manufacturing

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Abstract

Electronic skin (e-skin) has been widely used in various fields such as health monitoring, robotic tactile perception, and bioinspired prosthetics due to its ability to detect a wide range of signals. However, traditional flexible e-skin is limited in providing detailed information about the sensing surface and the velocity of surface fluid motion, which restricts its further applications. In this study, we successfully fabricated a bioinspired cilia-based e-skin that enables the sensing and detection of surface morphology, Braille, and airflow velocity. The bioinspired cilia exhibited a linear sensing range for static detection, with bending angles from 15° to 60°, and a frequency range of 1-25 Hz for dynamic sensing. A single cilia could accurately detect surface morphology changes as small as 0.5 mm and recognize Braille characters. Additionally, the cilia-based e-skin was capable of sensing and detecting airflow velocity. This multifunctional cilia-based e-skin integrates three major functions: static tactile sensing (10-22,000 Pa), dynamic sliding sensing (0.8-5.4 cm/s), and airflow sensing (1.8-5.7 m/s). This advancement holds promise for providing a novel approach to the multifunctional integration of flexible electronics.

Keywords

Cilia-based e-skin / surface morphology detection / airflow velocity detection / multifunctional bionic integration

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Jiangnan Yan, Jianing Ding, Yang Cao, Hongyu Yi, Limeng Zhan, Yifan Gao, Kongyu Ge, Hongjun Ji, Mingyu Li, Huanhuan Feng. Bioinspired cilia-based electronic skin for multimodal mechanical sensing via additive manufacturing. Soft Science, 2025, 5(2): 22 DOI:10.20517/ss.2025.03

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