Self‐Healing and Reprocessable Soft Robots Using 3D Digital Light Printing

This work advances 3D digital light printing of soft robots made from self‐healing, recyclable elastomers enabled by dynamic covalent bonds. With the introduction of room‐temperature healing, these robots recover their mechanical performance (94.5% static, 87.5% dynamic) after damage and maintain their functionality. The approach enables self‐healing, recyclable soft robots with complex geometries through additive manufacturing, thereby fostering sustainable and resilient robots for extreme environments. Abstract Soft robots manufactured from compliant materials are highly versatile and can interact safely with humans while performing complex tasks. However, their low modulus and high compliance make them vulnerable to mechanical damage. Here, we synthesise soft, self‐healing, and recyclable robots featuring complex air chambers using 3D digital light printing technology. The formulated monomers and cross‐linkers are polymerized layer‐by‐layer using photoinitiated free‐radical polymerization during the printing process to form soft objects on a moving metal substrate. Dynamic chemistry is introduced into the polymer by designing cross‐linker structures, whereby vinylogous urethanes‐bearing cross‐linkers of different chain lengths are studied to allow the cross‐linked elastomer networks to be thermally triggerable for self‐healing and reprocessing. The resultant elastomer exhibits a tensile strength of 3.51 ± 0.1 MPa and an elongation at break of 454 ± 56% with optimized formulations and printing parameters. The printed soft grippers and crawlers are investigated for their static and dynamic performance after being punctured, cut in half, and left to self‐heal at room temperature for 24 h. They exhibit excellent self‐healing capabilities with efficiencies of 94.5% and 87.5%, respectively. This new approach creates self‐healing, recyclable soft robots with complex geometries through additive manufacturing, enabling sustainable, resilient robots for challenging environments. This work advances 3D digital light printing of soft robots made from self-healing, recyclable elastomers enabled by dynamic covalent bonds. With the introduction of room-temperature healing, these robots recover their mechanical performance (94.5% static, 87.5% dynamic) after damage and maintain their functionality. The approach enables self-healing, recyclable soft robots with complex geometries through additive manufacturing, thereby fostering sustainable and resilient robots for extreme environments. Abstract Soft robots manufactured from compliant materials are highly versatile and can interact safely with humans while performing complex tasks. However, their low modulus and high compliance make them vulnerable to mechanical damage. Here, we synthesise soft, self-healing, and recyclable robots featuring complex air chambers using 3D digital light printing technology. The formulated monomers and cross-linkers are polymerized layer-by-layer using photoinitiated free-radical polymerization during the printing process to form soft objects on a moving metal substrate. Dynamic chemistry is introduced into the polymer by designing cross-linker structures, whereby vinylogous urethanes-bearing cross-linkers of different chain lengths are studied to allow the cross-linked elastomer networks to be thermally triggerable for self-healing and reprocessing. The resultant elastomer exhibits a tensile strength of 3.51 ± 0.1 MPa and an elongation at break of 454 ± 56% with optimized formulations and printing parameters. The printed soft grippers and crawlers are investigated for their static and dynamic performance after being punctured, cut in half, and left to self-heal at room temperature for 24 h. They exhibit excellent self-healing capabilities with efficiencies of 94.5% and 87.5%, respectively. This new approach creates self-healing, recyclable soft robots with complex geometries through additive manufacturing, enabling sustainable, resilient robots for challenging environments. Advanced Science, Volume 13, Issue 2, 9 January 2026.