Passive and active tracer dynamics in crowded environment:

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Using molecular dynamics simulations, we investigated tracer diffusion within a polymer matrix featuring specific, trap-like binding zones. Our simulations reveal that the tracer can undergo normal yet non-Gaussian diffusion under specific conditions—namely, when the trapped polymers are immobile and both the volume fraction and binding strength of the traps remain moderate. In this regime, the tracer experiences a heterogeneous environment, exhibiting motion akin to a confined continuous-time random walk (CTRW) that drives the non-Gaussian behavior. Furthermore, long-time dynamics shift to subdiffusive as trap density or binding strength increases. Conversely, when the polymers are mobile, the tracer dynamics remain Gaussian, though they can be normal or subdiffusive depending on trap parameters. We find that increasing the trap density, binding strength, or tracer size systematically enhances the trapping probability; notably, removing the binding zones eliminates trapping entirely, even under high crowding. For larger tracers in a frozen polymer background, the dynamics become highly subdiffusive but only weakly non-Gaussian. These observations align with recent experimental findings on tracer diffusion in polymeric materials, challenging the general validity of Gaussian theories in crowded environments. Building on this, our group has recently explored tracer diffusion in polymer gels—focusing on how tracer size, shape, and gel flexibility induce heavy-tailed, non-Gaussian dynamics. In addition we have also investigated the dynamics of active Janus probes in crowded environments, focusing on the translational-rotational decoupling observed at moderate crowding as well as methods to control the diffusion of non-magnetic active nanoparticles in magnetic fluids using external magnetic fields. More recently, we have started investigating the navigation strategy of soft active agents in porous media.

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