  Turbulent mixing is studied in the Lagrangian framework with an approach
based on the complex network formalism. We consider the motion of passive,
noninertial particles inside a turbulent channel simulated at $Re_{\tau} =
950$. The time-dependent network is built to evaluate the transfer of tracers
between thin wall-parallel layers which partition the channel in the
wall-normal direction. By doing so, we are able to assess the spatial and
temporal complexities arising from turbulence dynamics and their influence on
the mixing process. This approach highlights the effects of small-scale
features of turbulent flow structures and also the larger scale effects
determined by wall-induced anisotropy. Complex networks, coupled to the
Lagrangian description of turbulence, are effective in providing novel insights
into inhomogeneous turbulence and mixing.
