Session: 04-17-01: Functional Soft Composites - Design, Mechanics, and Manufacturing

Paper Number: 165967

Self-Healing Artificial Muscle: Mechanisms for Damage Detection and Autonomous Repair of Puncture Damage 

Soft robotics are characterized by their high deformability, mechanical robustness, and inherent resistance to damage. These unique properties present exciting new opportunities to enhance both emerging and existing fields such as healthcare, manufacturing, and exploration. However, for soft structures to function effectively in unstructured environments, these technologies must withstand the same real-world conditions that human skin and other soft biological materials experience. Human skin and nervous tissue serve as exemplary models of soft, responsive materials that can detect, communicate, and recover from injuries through their inherent plasticity. These characteristics are particularly relevant for soft robotic systems designed for agricultural applications, which exposure to sharp objects such as twigs, thorns, plastic, or glass can pose a risk of causing damage to these systems. To address this vulnerability, researchers have introduced self-healing polymeric and elastomeric materials for soft robotics applications that employ a variety of mechanisms, such as microcapsules, dynamic covalent bonds, or supramolecular chemistries, to achieve self-repair. However, these approaches often rely on manual intervention or external healing mechanisms to facilitate the self-healing process. Here, we introduce a novel soft material architecture for active detection of material damage and autonomous repair through in situ reprocessing and reconfiguration of both the material structure and its electrical network. This architecture includes a soft electronic skin composed of liquid metal (eutectic gallium indium) microdroplets embedded within a silicone elastomer. The liquid metal elastomer composite is naturally electrically insulating after curing due the presence of an insulating oxide skin on the surface of the liquid metal droplets and lack of droplet–droplet contact or percolating networks. However, the application of local pressure (> 1 MPa) or various modes of mechanical damage (e.g., cutting, puncture) can cause the liquid metal inclusions to rupture, forming a conductive percolating network that is internal to the composite. The damage-initiated change in electrical conductivity enables the detection and localization of damage events. The newly created conductive networks also serve as in situ Joule heating elements to facilitate the reprocessing and healing of physically cross-linked polymer layers. Following the self-healing process, these electrical networks can be reconfigured using controlled electrical and thermal mechanisms to create physical discontinuities. This system level integration enables electrical damage detection and localization, self-healing capabilities for extreme damage events, and the reconfiguration of newly formed electrical networks–all without the need for manual intervention or external healing mechanisms. This approach not only enhances the resilience and functionality of soft materials but also paves the way for advanced applications in soft robotics and wearable technologies, where adaptive and autonomous systems are essential for continuous operation in dynamic and unstructured environments.

Presenting Author: Eric Markvicka University of Nebraska

Presenting Author Biography: Dr. Eric Markvicka is the Robert F. and Myrna L. Krohn Assistant Professor of Mechanical and Materials Engineering at the University of Nebraska-Lincoln (UNL). There, he also holds a courtesy appointment in the School of Computing and the Department of Electrical and Computer Engineering. At UNL Prof. Markvicka directs the Smart Materials and Robotics Laboratory, an interdisciplinary research lab that is creating multifunctional soft materials that exhibit a unique combination of mechanical, electrical, acoustic, and thermal properties. These materials are critical components for the emerging fields of wearable computing, soft robotics, and robotic materials. Prof. Markvicka has is a senior member of the National Academy of Inventors and has received the 2024 NSF CAREER award, 2024 ASME Rising Star of Mechanical Engineering award, 2024 College of Engineering Edgerton Innovation Award, 2023 College of Engineering Excellence in Research Award, and 2021 NUtech Ventures Emerging Innovator of the Year award. Before joining the faculty at UNL, Eric received his B.S. and M.S. in Mechanical and Materials Engineering from UNL and his M.S. and Ph.D. in Robotics from Carnegie Mellon University.

Authors:

Eric Markvicka University of Nebraska