journal article·2022-11-22

Probing Fast Transformation of Magnetic Colloidal Microswarms in Complex Fluids

Shihao Yang, Qianqian Wang, Dongdong Jin, Xingzhou Du, Li Zhang

ACS Nano· Volume 16· Issue 11
Publisher page

Abstract

The rapidly transformed morphology of natural swarms enables fast response to environmental changes. Artificial microswarms can reconfigure their swarm patterns like natural swarms, which have drawn extensive attention due to their active adaptability in complex environments. However, as a prerequisite for biomedical applications of microswarms in confined environments, achieving on-demand control of pattern transformation rates remains a challenge. In this work, we report a strategy for optimizing pattern transformation rates of colloidal microswarms by coordinating the inner interactions. The influences of magnetic field parameters on pattern transformation rates are theoretically and experimentally studied, which elucidates the mechanism for optimal transformation rate control. The feasibility of the strategy is then validated in viscous Newtonian fluids and non-Newtonian biofluids. Moreover, the strategy is further validated in dynamic flow environments, exhibiting a promising future for practical applications in targeted delivery tasks with an optimal pattern transformation manner.
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Research context

OpenAlex topics: Micro and Nano Robotics · Pickering emulsions and particle stabilization · Advanced Materials and Mechanics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong999077, People’s Republic of China

Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing211100, People’s Republic of China

Department of Surgery, The Chinese University of Hong Kong, Hong Kong999077, People’s Republic of China

Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Hong Kong999077, People’s Republic of China

T Stone Robotics Institute, The Chinese University of Hong Kong, Hong Kong999077, People’s Republic of China

Multi-Scale Medical Robotics Center, Hong Kong Science Park, Hong Kong999077, People’s Republic of China

Funding

Research Grants Council, University Grants Committee · Natural Science Foundation of Jiangsu Province · Central University Basic Research Fund of China · Innovation and Technology Commission · Croucher Foundation · National Natural Science Foundation of China · Chinese University of Hong Kong · Joint Laboratory of Robotics and Intelligent Systems, Shenzhen Institute of Advanced Integration Technology · Joint Laboratory of Robotics and Intelligent Systems, Chinese University of Hong Kong

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