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

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 mu m. 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.

Automated summary

The tactile perception of fine textures in humans is mediated by fingertip skin, which is crucial for obtaining environmental information and manipulating objects precisely. Electronic skins based on triboelectric nanogenerator (TENG) have shown impressive applications in fine texture recognition by accurately mapping surface textures to electrical signals and revealing physical information. The fingerprint-inspired electronic skin (FE-skin) developed in this study can effectively detect and identify different textures by mimicking human fingerprints' morphology, achieving high accuracy rates in texture recognition through processing electrical signals with artificial neural networks. This technology demonstrates TENG's potential superiority in bionic tactile perception and has broad application prospects in humanoid robots, intelligent prostheses, and precise human-machine interaction.