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Active generation and magnetic actuation of microrobotic swarms in bio-fluids

Author

Listed:
  • Jiangfan Yu

    (The Chinese University of Hong Kong)

  • Dongdong Jin

    (The Chinese University of Hong Kong)

  • Kai-Fung Chan

    (The Chinese University of Hong Kong)

  • Qianqian Wang

    (The Chinese University of Hong Kong)

  • Ke Yuan

    (The Chinese University of Hong Kong)

  • Li Zhang

    (The Chinese University of Hong Kong
    The Chinese University of Hong Kong
    The Chinese University of Hong Kong
    The Chinese University of Hong Kong)

Abstract

In nature, various types of animals will form self-organised large-scale structures. Through designing wireless actuation methods, microrobots can emulate natural swarm behaviours, which have drawn extensive attention due to their great potential in biomedical applications. However, as the prerequisite for their in-vivo applications, whether microrobotic swarms can take effect in bio-fluids with complex components has yet to be fully investigated. In this work, we first categorise magnetic active swarms into three types, and individually investigate the generation and navigation behaviours of two types of the swarms in bio-fluids. The influences of viscosities, ionic strengths and mesh-like structures are studied. A strategy is then proposed to select the optimised swarms in different fluidic environments based on their physical properties, and the results are further validated in various bio-fluids. Moreover, we also realise the swarm generation and navigation in bovine eyeballs, which also validates the proposed prediction in the ex-vivo environment.

Suggested Citation

  • Jiangfan Yu & Dongdong Jin & Kai-Fung Chan & Qianqian Wang & Ke Yuan & Li Zhang, 2019. "Active generation and magnetic actuation of microrobotic swarms in bio-fluids," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13576-6
    DOI: 10.1038/s41467-019-13576-6
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    Cited by:

    1. Jayraj V. Vaghasiya & Carmen C. Mayorga-Martinez & Stanislava Matějková & Martin Pumera, 2022. "Pick up and dispose of pollutants from water via temperature-responsive micellar copolymers on magnetite nanorobots," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Gaurav Gardi & Steven Ceron & Wendong Wang & Kirstin Petersen & Metin Sitti, 2022. "Microrobot collectives with reconfigurable morphologies, behaviors, and functions," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Xiong Yang & Rong Tan & Haojian Lu & Toshio Fukuda & Yajing Shen, 2022. "Milli-scale cellular robots that can reconfigure morphologies and behaviors simultaneously," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Shuqin Chen & Xander Peetroons & Anna C. Bakenecker & Florencia Lezcano & Igor S. Aranson & Samuel Sánchez, 2024. "Collective buoyancy-driven dynamics in swarming enzymatic nanomotors," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Zhongguo Ren & Chen Xin & Kaiwen Liang & Heming Wang & Dawei Wang & Liqun Xu & Yanlei Hu & Jiawen Li & Jiaru Chu & Dong Wu, 2024. "Femtosecond laser writing of ant-inspired reconfigurable microbot collectives," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    6. Sukyoung Won & Hee Eun Lee & Young Shik Cho & Kijun Yang & Jeong Eun Park & Seung Jae Yang & Jeong Jae Wie, 2022. "Multimodal collective swimming of magnetically articulated modular nanocomposite robots," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

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