Fingerprint-inspired electronic skin based on triboelectric nanogenerator for fine texture recognition

• Published in: Nano energy Vol. 85; p. 106001
• Main Authors: Zhao, Xuan, Zhang, Zheng, Xu, Liangxu, Gao, Fangfang, Zhao, Bin, Ouyang, Tian, Kang, Zhuo, Liao, Qingliang, Zhang, Yue
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2021
• Subjects: Artificial neural network; Electronic skin; Fingerprint-inspired; Texture recognition; Triboelectric nanogenerator; Triboelectric nanogenerator; Electronic skin; Artificial neural network; Fingerprint-inspired; Texture recognition
• DOI: 10.1016/j.nanoen.2021.106001
• ISSN: 2211-2855

In humans, fine textures' tactile perception is mediated by fingertip skin, which is essential for environmental information obtaining and precision manipulation of objects. The keys to replicating the dynamic tactile perception ability in artificial devices are how to accurately map surface textures to electrical signals and reveal physical information. Electronic skins based on triboelectric nanogenerator (TENG) have obtained many impressive applications and have great potential in fine texture recognition. Here, we built a fingerprint-inspired electronic skin (FE-skin) based on TENG that can respond to fine textures by the biomimetic design of human fingerprints' morphology. The FE-skin can detect the change of the contact area caused by the dynamic interaction between the fingerprint structure and the tested object surface, and the minimum size of the texture that can be discerned is as low as 6.5 µm. Besides, different textures can be effectively identified by processing the collected electrical signals via artificial neural networks. In the recognition demonstration of disordered and ordered texture, the accuracy rates of over 93.33% and 92.5% were obtained, respectively. This technology demonstrates TENG's potential superiority in the field of bionic tactile perception and has broad application prospects in humanoid robots, intelligent prostheses, and precise human-machine interaction. [Display omitted] •Fingerprint-inspired electronic skin based on single-electrode TENG for fine texture recognition.•Artificial neural networks for classifying the collected signals.•Successful demonstration of the recognition of surface roughness and Braille.