SPINS: Spin crossover Polymers IN Softwareless Soft robots

Objective

Although spin-crossover (SCO) composites are increasingly studied in academia, including for soft-robot actuation, due to their unique stimuli-responses, real-world applications remain absent. This is mainly due to (i) limited understanding of structure–property relations needed to tailor SCO composites for applications, and (ii) inherent drawbacks of SCO-based actuation, such as low force output, small deformations, and slow dynamics. This interdisciplinary SPINS project addresses these challenges by (i) developing a comprehensive toolbox for designing SCO composites, linking matrix composition, filler type, loading, dispersion, and orientation to their mechanical, thermal, and responsive properties (transition temperature, anisotropy, hysteresis), and (ii) for the first time, repositioning SCO composites in soft robotics from basic actuators/sensors to hardware-encoded adaptation components within fluidically actuated systems. By exploiting programmable transition temperature, hysteresis, and anisotropy to achieve thermal latch/unlatch behavior, the project combines fast and powerful actuation with autonomous adaptation. This will enable a new class of electronic- and software-free soft robots that generate complex motions and adapt to external stimuli—such as temperature—solely through the intrinsic interaction of SCO composites with their environment. To achieve this, soft robotic structural, actuation, and logic units will be constructed from SCO composites, leveraging their stimuli-responsive behavior to achieve adaptable characteristics. Next, SPINS will establish design principles for combining these SCO-based units in soft robots, enabling systems that autonomously adjust geometry, actuation profiles, and gait patterns in response to stimuli. Consequently, this work will provide a framework for the NextGen of truly material-driven soft robots, while illustrating the broader potential of SCO composites in applications that exploit such physical computation.