Deep-Learning Enabled Active Biomimetic Multifunctional Hydrogel Electronic Skin

TLDR

There is a strong demand to replicate human skin’s epidermal and dermal functions for physical interactions. The study proposes a biomimetic, ultrasensitive, multifunctional hydrogel-based electronic skin (BHES). The BHES mimics epidermis with wrinkled PET enabling contact electrification, incorporates interdigital silver electrodes for stick–slip texture sensing, and uses patterned microcone hydrogel for pressure sensing with high sensitivity, wide range, low detection limit, and fast response. Deep learning enabled the BHES to identify 10 materials with 95 % accuracy and 4 textures with 97.2 % accuracy, and its integrated signal circuits demonstrated a wearable drone control system with three‑degree‑of‑freedom movement, indicating strong potential for soft robotics and human–machine interfaces.

Abstract

There is huge demand for recreating human skin with the functions of epidermis and dermis for interactions with the physical world. Herein, a biomimetic, ultrasensitive, and multifunctional hydrogel-based electronic skin (BHES) was proposed. Its epidermis function was mimicked using poly(ethylene terephthalate) with nanoscale wrinkles, enabling accurate identification of materials through the capabilities to gain/lose electrons during contact electrification. Internal mechanoreceptor was mimicked by interdigital silver electrodes with stick–slip sensing capabilities to identify textures/roughness. The dermis function was mimicked by patterned microcone hydrogel, achieving pressure sensors with high sensitivity (17.32 mV/Pa), large pressure range (20–5000 Pa), low detection limit, and fast response (10 ms)/recovery time (17 ms). Assisted by deep learning, this BHES achieved high accuracy and minimized interference in identifying materials (95.00% for 10 materials) and textures (97.20% for four roughness cases). By integrating signal acquisition/processing circuits, a wearable drone control system was demonstrated with three-degree-of-freedom movement and enormous potentials for soft robots, self-powered human–machine interaction interfaces of digital twins.