2005
DOI: 10.1080/08927020500423778
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Effect of surface roughness on slip flows in hydrophobic and hydrophilic microchannels by molecular dynamics simulation

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Cited by 30 publications
(32 citation statements)
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“…In a previous study (Yang and Fang 2005), MD simulations were performed to investigate the parameters controlling the degree of slip, the dependence of slip length, and the shear rate for simple fluids with atomic surface roughness in hydrophobic and hydrophilic microchannels. In the current work, the flow behavior and the slip length are examined for simple fluids confined between two parallel solid walls.…”
Section: Simulation Methodsmentioning
confidence: 99%
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“…In a previous study (Yang and Fang 2005), MD simulations were performed to investigate the parameters controlling the degree of slip, the dependence of slip length, and the shear rate for simple fluids with atomic surface roughness in hydrophobic and hydrophilic microchannels. In the current work, the flow behavior and the slip length are examined for simple fluids confined between two parallel solid walls.…”
Section: Simulation Methodsmentioning
confidence: 99%
“…The purpose of this paper is to examine the effects of surface wettability and roughness of the surface on the nanoscale flow behavior and the boundary slip by MD simulation. The nanoscale roughness of the surface considered in this study is characterized by the solid wall decorated with periodic nanostrips on the surface, which is different from those in Yang and Fang (2005). The dependence of wall slip and flow rate is also discussed with various boundary conditions.…”
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confidence: 98%
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“…The choice is based on the evidence 82,83 that the slip length δ depends on the wettability as δ ∝ 1/ε 2 , and we expect the similar dependence for ∆R. In addition the dependence of ∆R on the capillary roughness (13) shows a linear decay 84 suggesting that the difference ∆R can be expressed as Here ∆R 0 is the asymptotic value of ∆R for ε → ∞ and R → 0 and k ε , k R are numerical coefficients. k ε = 5.07 ± 1.01 was obtained by fitting the data in 12, and k R = −1.00±0.18 by fitting the data in 13.…”
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confidence: 99%