Gu Zhaoqi, Zhu Runlin, Shen Tianci, Dou Lin, Liu Hongjiang, Liu Yifei, Liu Xu, Liu Jia, Zhuang Songlin, Gu Fuxing
Laboratory of Integrated Opto-Mechanics and Electronics, Shanghai Key Laboratory of Modern Optical System, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, 200093, Shanghai, China.
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, 300130, Tianjin, China.
Nat Commun. 2023 Nov 24;14(1):7663. doi: 10.1038/s41467-023-43433-6.
Nanorobotic motion on solid substrates is greatly hindered by strong nanofriction, and powerful nanomotors‒the core components for nanorobotic motion‒are still lacking. Optical actuation addresses power and motion control issues simultaneously, while conventional technologies with small thrust usually apply to fluid environments. Here, we demonstrate micronewton-thrust nanomotors that enable the autonomous nanorobots working like conventional robots with precise motion control on dry surfaces by a photothermal-shock technique. We build a pulsed laser-based actuation and trapping platform, termed photothermal-shock tweezers, for general motion control of metallic nanomaterials and assembled nanorobots with nanoscale precision. The thrust-to-weight ratios up to 10 enable nanomotors output forces to interact with external micro/nano-objects. Leveraging machine vision and deep learning technologies, we assemble the nanomotors into autonomous nanorobots with complex structures, and demonstrate multi-degree-of-freedom motion and sophisticated functions. Our photothermal shock-actuation concept fundamentally addresses the nanotribology challenges and expands the nanorobotic horizon from fluids to dry solid surfaces.
纳米机器人在固体基底上的运动受到强大的纳米摩擦力的极大阻碍，而且用于纳米机器人运动的核心组件——强大的纳米马达仍然匮乏。光驱动同时解决了动力和运动控制问题，而通常具有小推力的传统技术则适用于流体环境。在此，我们展示了微牛顿推力的纳米马达，其通过光热冲击技术使自主纳米机器人能够像传统机器人一样在干燥表面上进行精确运动控制。我们构建了一个基于脉冲激光的驱动和捕获平台，称为光热冲击镊子，用于对金属纳米材料和组装好的纳米机器人进行具有纳米级精度的一般运动控制。高达10的推重比使纳米马达能够输出力以与外部微/纳米物体相互作用。利用机器视觉和深度学习技术，我们将纳米马达组装成具有复杂结构的自主纳米机器人，并展示了多自由度运动和复杂功能。我们的光热冲击驱动概念从根本上解决了纳米摩擦学挑战，并将纳米机器人的应用范围从流体扩展到干燥的固体表面。
