Digital Light Processing of Soft Robotic Gripper with High Toughness and Self‐Healing Capability Achieved by Deep Eutectic Solvents
Cong‐Wei Huang, Si‐Chun Wen, Chuan‐Hsun Hsiao, Chen‐Zhen Zhang, Kuan‐Chung Lin, Shengsheng Yu
- 发表年份
- 2024
- 引用次数
- 27
- 访问权限
- 开放获取
摘要
Abstract Inspired by nature's flexible and adaptable organisms, soft robotics are motorless robots made from highly compliant materials to work in confined environments and manipulate delicate objects. However, soft robots often suffer from early failure because of unexpected damage. At the same time, it is challenging to manufacture the geometrically complex structures of soft robots. This study introduces resins based on deep eutectic solvents (DES) to fabricate a pneumatically driven soft gripper using digital light processing (DLP). The resins consist of choline chloride (ChCl) as a hydrogen bond acceptor, glycerol (Gly), and acrylamide (AAm) as hydrogen bond donors. By utilizing the intense hydrogen bonding within DES, the resin can be rapidly cured by photopolymerization to form tough ionogels without chemical crosslinkers. The DES ionogels exhibit remarkable toughness and self‐healing performance compared to common hydrogels. Furthermore, the ionogels show not only efficient energy‐dissipating behavior but also achieve rapid self‐recovery. Finally, the DLP‐printed soft gripper from the DES‐based resin performs successful actuation and healing of macroscopic damages. This work presents a simple strategy to 3D print a soft robotic gripper with high toughness and self‐healing capability.
关键词
相关论文
Artificial intelligence: a modern approach
1995
Self-Organizing Maps
Teuvo Kohonen
1995
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller 等 4 位作者
2013
Probabilistic robotics
Sebastian Thrun
2002