Electroosmotic Flow in a Rough Nanochannel with Surface Roughness Characterized by Fractal Cantor

Abstract

Molecular dynamics simulation is applied to study the electroosmotic flow in rough nanochannels, with particular attention given to the fluid–solid interactions. In the simulation, the surface roughness is characterized by a fractal Cantor. The roles of roughness height and fractal dimension on nanoscale electroosmotic flow are examined and analyzed. The concentration distributions, zeta potential and electroosmotic velocity are presented and investigated. The results indicate that surface roughness plays a significant role in the fluid–solid interaction and nanoscale electroosmotic flow. The distribution of dipole angle for water molecules in both the near-wall region and middle region is almost unaffected by surface roughness; however, a significant difference of dipole angle distribution is observed in the fluid region away from the wall. Interestingly, the concentration distributions, electroosmotic velocity and zeta potential are highly affected by the surface fractal dimension, even with the same roughness height.

Effect of Water Models on Transmembrane Self-Assembled Cyclic Peptide Nanotubes

“…Water molecules in the nanoconfined environment provided by natural or artificial membrane channels deserve special attention, because they are expected to behave significantly differently from those in bulk solution and at interfaces. , Simplified models of nanotubes and nanopores have been extensively studied in terms of the behavior of nanoconfined water within their cavities, using both continuum fluid dynamics (CFD) theory and molecular dynamics (MD) simulations. − Perhaps surprisingly, continuum models (modified by insights from atomistic MD simulations) have provided reasonable descriptions of the behavior of water in simple nanopores. Even with continuum models, the influence of the internal shape and hydrophobicity of the channels has been demonstrated. − For example, studies carried out by Gravelle et al with models of aquaporins concluded that the internal geometry of the channel plays a role, suggesting that structures which reduce the surface friction, as for example in an hourglass shape, favor water permeability when compared with cylindrical channels. , However, it has been suggested that the accuracy of the continuum models depends on the hydrophobicity and size of the pore, such that water flow is underestimated for small hydrophobic pores (<1 nm). , For small pores, the structural and dynamical properties of water are strongly influenced by interactions with the pore-lining interfaces, and thus, the detailed chemical properties of the pores become more important in determining water behavior. It is likely that for the design of nanopores and in order to understand complex biological nanopores, accurate atomistic simulations of water properties are required.…”

Editorial for the Special Issue on Micro/Nano-Chip Electrokinetics, Volume II

“…Matías et al [ 10 ] presented a perturbation analysis of Joule heating effects on electroosmotic flow in a microcapillary tube filled with immiscible Newtonian and power-law fluids. Lu et al [ 11 ] used a molecular dynamics simulation to study the electroosmotic flow in rough nanochannels, with particular attention to the fluid–solid interactions. Lim et al [ 12 ] developed a technique to fabricate microchannels with black silicon nanostructures for a controllable suppression of electroosmotic flow.…”

Temperature-Dependent Electro-osmotic Flow Reversal in a Nanotube with High Surface Charge Density

“…The parameters used in the continuum model calculation need to be extracted on the basis of molecular dynamics simulation in order to make the simulation results fit well with the continuum prediction results . Accordingly, the molecular dynamics (MD) simulation, which is one particle-based method, has proved to be promising in the prediction of nanoscale flows. , The objective of the MD simulation is to consider the interactions between atoms and solve Newton’s equations for each particle to extract the thermodynamics properties. One of the most important advantages of MD simulation is its ability to predict the behavior of ions in the Stern layer, which can perform a more accurate analysis as the separate regions of the EDL (the Stern layer and the diffuse layer) are considered.…”