Deep‐Learning‐Assisted Thermogalvanic Hydrogel E‐Skin for Self‐Powered Signature Recognition and Biometric Authentication

Abstract Self‐powered electronic skins (e‐skins), as on‐skin human‐machine interfaces, play a significant role in cyber security and personal electronics. However, current self‐powered e‐skins are primarily constrained by complex fabricating process, intrinsic stiffness, signal distortion under deformation, and inadequate comprehensive performance, thereby hindering their practical applications. Herein, a novel highly stretchable (534.5%), ionic conductive (4.54 S m −1 ), thermogalvanic (1.82 mV K −1 ) hydrogel (TGH) is facilely fabricated by a one‐pot method. Owing to the formation of Li + (H 2 O) n hydration structure, the TGH presents excellent anti‐freezing and non‐drying performance. It remains flexible…

• SI
  Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering

  Award: 2022SX‐TD022
• NS
  Natural Science Foundation of Shanxi Province

  Award: 20210302123190