Shape referencing in reconfigurable beams via adaptive electroactive material systems

This research introduces a novel paradigm in autonomous reconfigurable material systems by leveraging liquid crystal elastomer (LCE) actuators for shape referencing in reconfigurable beams. The approach integrates sensing, processing, memory, and actuation capabilities to develop foundations for intelligence in material systems. The methodology utilizes stimuli-responsive materials such as electroactive LCE actuators with a silver thermoplastic polyurethane (Ag-TPU) heating element to enable self-adaptive behavior. A bistable 1-bit unit cell is the foundational element, showcasing successful toggling between binary ‘0’ and ‘1’ states. Logical functions are used to develop an electro-mechanical network on a multi-cell system. The proof-of-concept prototype demonstrates the feasibility of embedding autonomous behavior into beams. Using programmable logic, the prototype can adapt and mirror the shape changes of a reference configuration. The research presents a versatile and adaptive approach that expands the potential applications of autonomous intelligent material systems.