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Title |
Fingerpad-Inspired Multimodal Electronic Skin for Material Discrimination and Texture Recognition |
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Author list |
Giwon Lee, Jong Hyun Son, Siyoung Lee, Seong Won Kim, Daegun Kim, Nguyen Ngan Nguyen, Seung Goo Lee, and Kilwon Cho |
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Publication date |
2021/05 |
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Citation information |
Advacend Science, 8, 2002606 (2021)
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DOI |
10.1002/advs.202002606 |
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Graphical Abstract |
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Abstract |
Human skin plays a critical role in a person communicating with his or her environment through diverse activities such as touching or deforming an object. Various electronic skin (E-skin) devices have been developed that show functional or geometrical superiority to human skin. However, research into stretchable E-skin that can simultaneously distinguish materials and textures has not been established yet. Here, the first approach to achieving a stretchable multimodal device is reported, that operates on the basis of various electrical properties of piezoelectricity, triboelectricity, and piezoresistivity and that exceeds the capabilities of human tactile perception. The prepared E?kin is composed of a wrinkle?atterned silicon elastomer, hybrid nanomaterials of silver nanowires and zinc oxide nanowires, and a thin elastomeric dielectric layer covering the hybrid nanomaterials, where the dielectric layer exhibits high surface roughness mimicking human fingerprints. This versatile device can identify and distinguish not only mechanical stress from a single stimulus such as pressure, tensile strain, or vibration but also that from a combination of multiple stimuli. With simultaneous sensing and analysis of the integrated stimuli, the approach enables material discrimination and texture recognition for a biomimetic prosthesis when the multifunctional E-skin is applied to a robotic hand. |
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