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[Microfluidics and Nanofluidics]Spatial distribution of conductivity in a short charged nanofluidic pore

March 7, 2017

Abstract:

 

There is very little information about the spatial distribution of conductivity in nanopores. We calculated linearized conductivity from potential and current changes estimated by Poisson–Nernst–Planck and Navier–Stokes simulations of ion transport. The conductivity changes radially and axially. It is elevated near the wall of charged pores (or uncharged pores in the presence of electric field) with homogeneous diffusion within the nanopore, but is depressed if diffusion is slower near the wall. In unipolar nanopores, it is high in charged and uncharged half (regular bias), or moderate in the charged and low in uncharged half (reverse bias). In bipolar nanopores, the conductivity is high in both halves (but dips in the middle near the wall; regular bias). With reverse bias, it is very low throughout the nanopore, but the 3D resistivity plots reveal the resistivity to be much higher in the middle of the nanopore, critically influencing the pore resistance. Its restricted axial spread demonstrates that bipolar cylindrical nanofluidic diodes can be highly miniaturized.

 

Graphical Abstract:

 

Both pore wall charge distribution and voltage bias affect the total conductivity of the nanopore, and its spatial distribution. As shown in unipolar nanopores the conductivity is high in charged and uncharged half (regular bias), or moderate in the charged and low in uncharged half (reverse bias) with homogeneous diffusion, but diminishes near the wall if diffusion becomes inhomogeneous, especially in the uncharged half (not shown). In bipolar nanopores, the conductivity is high within the nanopore, but dips near the wall in the middle, i.e., where the charges of opposite polarity meet (regular bias) with homogeneous diffusion, but decreases near the wall if diffusion becomes inhomogeneous (not shown). If the bias is reverse, the conductivity is very low throughout the nanopore irrespective of whether diffusion is homogeneous or inhomogeneous.

 

Mohammad Tajparast, Hossein Mohammadi, Mladen I. Glavinović

 

Tajparast, M., Mohammadi, H. & Glavinović, M.I. Microfluid Nanofluid (2017) 21: 49. doi:10.1007/s10404-017-1884-9

 

Link: https://link.springer.com/article/10.1007/s10404-017-1884-9

 

 

 

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