Self-healing electro-optical skin for dual-mode human-machine interaction

Abstract

Scenario-adaptive electronic skins (e-skins) are significant for improving human-machine-environment interaction. Realizing high-performance e-skins with electro-optical cooperative perceptivity (EO-skin) for mechanical stimuli monitoring remains challenging. Herein, utilizing microphase separated styrene-isoprene-styrene and ethyl vinyl acetate (SIS-EVA) as elastomer matrix, we demonstrate a stretchable, adhesive, and self-healable mechanoluminescent tactile EO-skin with triboelectric self-powered perceptivity. The EO-skin possesses a seamlessly integrated tri-layer structure by interface etching and self-binding effect in continuous casting, where the top mechanoluminescent layer (SIS-EVA embedded with ZnS/CaZnOS:Mn²⁺ particles) adheres to an electrode layer consisting of SIS-EVA/silver flakes/liquid metal microparticles are encapsulated by an SIS-EVA substrate. This EO-skin can visualize mechanical stimuli (emit orange-yellow light) and generate triboelectric signals (~65 V), demonstrating an electro-optical dual-mode interactive e-skin for tactile sensing to identify material textures, and touching/writing information. The EO-skin is adaptive to different surfaces (~2.49 MPa adhesive strength), highly stretchable (tensile strain ~1040%) and self-healable (93% mechanical healing efficiency) with stable electro-optical performances. In addition to traditional electrical tactile identification, dynamic optical capturing-based machine learning was used to build an electro-optical dual-mode human-machine interactive system for high-precision handwritten information identification (~97.76%). This self-healable EO-skin with electro-optical dual-mode sensing capability promises to realize multidimensional mechanical-adaptive human-machine interactions in specific scenarios.