Gradient-Microstructure Synergy for Self-Powered Ionic Skins with Ultrahigh Sensitivity

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Authors: Guotong Sun, Wenxin Fan, Hongen Chen, Jianzhang Li, Kunyan Sui
Cited by: 3
References: 52

Abstract

In the era of the Internet of Things and artificial intelligence, energy-efficient self-powered ionic skins are urgently needed, yet existing ionic skins suffer from limited sensitivity, resulting in poor ability to detect subtle pressure changes. Herein, we report a versatile gradient-microstructure synergy (GMS) strategy to engineer ionogels with both charge gradients and surface wrinkles, enabling self-powered ionic skins with ultrahigh sensitivity. The sharp charge gradient and surface wrinkles are sequentially constructed via a facile ultraviolet-initiated radical polymerization and a stretching/coordinating/releasing method, respectively. The sharp charge gradient endows the ionic skin with outstanding self-powered sensing capability, which, together with the wrinkled surface, substantially enhances sensitivity by amplifying interfacial potential variation between the wrinkled gradient ionogel and the electrodes. Consequently, the as-prepared wrinkled gradient ionic skins operate in self-powered mode with an ultrahigh sensitivity of 368.32 kPa –1, far surpassing that of previously reported self-powered ionic skins. The self-powered ionic skins also exhibit exceptional sensing stability and outstanding mechanical properties, enabling real-time detection of various human motions, physiological activities, and subtle mechanical vibrations. The proposed GMS strategy thus offers a robust platform for the rational design and scalable fabrication of high-performance self-powered ionic skins, facilitating their practical deployment.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Advanced Materials and Mechanics Dielectric materials and actuators

Publication details

Journal / source
ACS Applied Materials & Interfaces
Publisher
American Chemical Society (ACS)
Volume
18
Issue
26
Pages
37103–37112
Publication date
25 June 2026
Language
EN