Demonstrates an innovative soft actuator that improves light harvesting efficiency in robotic systems, suggesting a new approach to energy autonomy.
Robotic systems’ mobility is fundamentally constrained by their power sources and wiring requirements. While electrical actuation systems have achieved autonomy through battery power and wireless control, pneumatic actuators remain tethered to air supply sources. Liquid-to-gas phase change actuators utilizing low-boiling-point liquids offer a potential solution, though they typically require substantial thermal input through heating elements that maintain electrical dependencies. External heat sources, particularly light energy, present an alternative for terrestrial applications. However, despite their optical transparency, silicone-based materials have a high volumetric heat capacity and low thermal conductivity, which limits efficient photothermal energy transfer. Previous attempts to address this issue through the incorporation of graphene or metallic powder have compromised material properties, including reduced transparency and altered elastic moduli. Inspired by the tapetum lucidum structure found in the eyes of nocturnal animals, which enables efficient light utilization in low-light conditions, this study proposes a novel anisotropic bilayer soft actuator incorporating Laser-Induced Graphene (LIG) on the inner surface of the light-irradiated silicone layer. This creates an anisotropic structure with enhanced photothermal conversion capabilities while maintaining the advantageous properties of silicone. Comparative analysis demonstrates that the proposed actuator exhibits significantly higher photo-induced bending efficiency than conventional silicone-based actuators. The response time improved by 54%, decreasing from 142 s for pure silicone to 65 s, with recovery response time showing a 48% improvement. This design maintains the silicone’s transparency and flexibility while utilizing LIG, which can be fabricated under ambient conditions, facilitating manufacturing and diverse applications.
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Sogabe et al. (2026) studied this question.
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