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Xue C D, Zheng X, Hu G Q. Anomalous Diffusion and Manipulation of Nanoparticles in Complex Fluid Environments. Advances in Mechanics, in press doi: 10.6052/1000-0992-26-004
Citation: Xue C D, Zheng X, Hu G Q. Anomalous Diffusion and Manipulation of Nanoparticles in Complex Fluid Environments. Advances in Mechanics, in press doi: 10.6052/1000-0992-26-004
shu

Anomalous Diffusion and Manipulation of Nanoparticles in Complex Fluid Environments

doi: 10.6052/1000-0992-26-004 cstr: 32046.14.1000-0992-26-004
  • 1.

    Dalian University of Technology, Dalian 116024, China

  • 2.

    Zhejiang University, Hangzhou 310058, China

  • 3.

    Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China

More Information
  • Corresponding author: ghu@zju.edu.cn
  • Received Date: 2026-01-24
  • Accepted Date: 2026-05-15
    • Available Online: 2026-06-02
    Abstract
  • The diffusive behavior of nanoparticles in complex fluid environments is widely observed in natural and industrial processes. In contrast to classical Brownian diffusion, nanoparticles in complex fluids exhibit anomalous diffusion characteristics. Understanding its mechanisms and developing control approaches hold significant scientific importance and application value across fields such as biology, physics, medicine, and engineering. This article provides a systematic review of the research progress on anomalous diffusion of nanoparticles in complex fluid environments. First, the core features of anomalous diffusion that go beyond classical Brownian motion are elucidated, and the main theoretical frameworks and research methods are outlined. Second, mechanisms and models of three specific anomalous diffusion, i.e., subdiffusion, superdiffusion, and Brownian yet non-Gaussian diffusion, are introduced in detail. The regulation mechanisms of diffusion behavior based on external field effects and intelligent design are also explored from the perspective of coupling mechanics and statistical physics. Finally, key challenges and future directions in modeling, experimental analysis, and applications in this field are summarized.

     

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