High-Speed and High-Resolution 3D Printing of Self-Healing and Ion-Conductive Hydrogels via μCLIP

Conductive and self-healing (SH) hydrogels have been receiving continuous attention, which could broaden the design of ionotronic devices for health monitoring systems and soft robots with the ability to repair damage autonomously. So far, three-dimensional (3D) fabrication of such SH hydrogels is mainly limited to traditional molding/casting or extrusion-based 3D printing methods, which limits the formation of sophisticated structures with high-resolution features. Furthermore, the need of external stimuli (e.g., water, heat, and pH change) to achieve SH behavior could restrict their wide application. Herein, we report an ion-conductive SH hydrogel suitable for a home-built high-resolution and high-speed 3D printing process, micro continuous liquid interface production (μCLIP). This material system relies on interpenetrating polymer networks (IPN) hydrogel formed by physically cross-linked poly(vinyl alcohol) combined with chemically/ionically cross-linked poly(acrylic acid) and ferric chloride. By carefully optimizing the resin’s composition, we can balance high-resolution printability and superb SH capability, at the same time manifesting sufficient ion conductivity. Specifically, complex 3D structures with microscale features (down to 100 μm) can be printed at speeds up to 16.5 μm s^-1. Upon damage occurs, hydrogen bonds within hydroxyl and carboxyl groups, as well as ionic bonds generated from ferric ions, contribute together to achieve fast and high efficiency SH, which can restore 90% (100%) of the original mechanical strength at room temperature within 4 h (8 h) without any external stimulus. In addition, both the as-printed and self-healed hydrogels manifest superior ion conductivity and stretchability. Therefore, the SH hydrogels can be rapidly printed and tailored as customized wearable sensors, and the sensing capabilities were quantitatively investigated and compared. In terms of applications, SH hydrogel-based knuckle sensors were prototyped to detect a finger’s folding and unfolding motions.