Focused ultrasound enables selective actuation and Newton-level force output of untethered soft robots.

Journal: Nature communications
PMID:

Abstract

Untethered miniature soft robots have significant application potentials in biomedical and industrial fields due to their space accessibility and safe human interaction. However, the lack of selective and forceful actuation is still challenging in revolutionizing and unleashing their versatility. Here, we propose a focused ultrasound-controlled phase transition strategy for achieving millimeter-level spatially selective actuation and Newton-level force of soft robots, which harnesses ultrasound-induced heating to trigger the phase transition inside the robot, enabling powerful actuation through inflation. The millimeter-level spatial resolution empowers single robot to perform multiple tasks according to specific requirements. As a concept-of-demonstration, we designed soft robot for liquid cargo delivery and biopsy robot for tissue acquisition and patching. Additionally, an autonomous control system is integrated with ultrasound imaging to enable automatic acoustic field alignment and control. The proposed method advances the spatiotemporal response capability of untethered miniature soft robots, holding promise for broadening their versatility and adaptability.

Authors

  • Bo Hao
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.
  • Yue Dong
    Department of Anesthesiology, Mayo Clinic College of Medicine, Rochester, MN, United States.
  • Mengmeng Sun
  • Chen Xin
    Hefei National Laboratory for Physical Sciences at the Microscale, Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, CAS Key Laboratory of Mechanical Behavior and Design of Materials, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
  • Haojin Yang
    Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, SAR 999077, PR China.
  • Yanfei Cao
    1 College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
  • Jiaqi Zhu
    State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Xurui Liu
    School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.
  • Chong Zhang
    Department of Big Data Management and Application, School of International Economics and Management, Beijing Technology and Business University, Beijing 100048, China.
  • Lin Su
  • Bing Li
  • Li Zhang
    Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.