Abstract
The slip boundary condition for nanoflows is a key component of nanohydrodynamics theory, and can play a significant role in the design and fabrication of nanofluidic devices. In this review, focused on the slip boundary conditions for nanoconfined liquid flows, we firstly summarize some basic concepts about slip length including its definition and categories. Then, the effects of different interfacial properties on slip length are analyzed. On strong hydrophilic surfaces, a negative slip length exists and varies with the external driving force. In addition, depending on whether there is a true slip length, the amplitude of surface roughness has different influences on the effective slip length. The composition of surface textures, including isotropic and anisotropic textures, can also affect the effective slip length. Finally, potential applications of nanofluidics with a tunable slip length are discussed and future directions related to slip boundary conditions for nanoscale flow systems are addressed.
Highlights
A basic postulate in the study and design of macroscopic fluidic systems based on the knowledge of fluid mechanics is that the no-slip boundary condition is valid at the solid–liquid interface [1]
When the liquid is at equilibrium, the viscous shear stress is exerted by the liquid on the wall, where η is the shear viscosity of the liquid, equal to the friction stress suffered by the liquid from the wall, which is expressed as σ = λνs, where λ represents the interfacial friction coefficient [46]
For a negative apparent slip length, or negative slip length for short, the no-slip boundary condition holds at the liquid–liquid interface with a thin immobile liquid layer in the vicinity of the solid surface
Summary
A basic postulate in the study and design of macroscopic fluidic systems based on the knowledge of fluid mechanics is that the no-slip boundary condition is valid at the solid–liquid interface [1]. The methods to investigate slip boundary conditions for nanoconfined liquids include theoretical analysis, physical experiments, and numerical simulations [8,24,25,26,27,28,29,30,31,32,33,34]. Machine learning methods have been applied in the study of dynamic properties of liquids including diffusion and slip flow behavior, and in the prediction of the slip length at the nanoscale [35,36,37]. In this review we mainly focus on the numerical investigations and theoretical analysis on slip boundary conditions for nanoscale liquid transport. The conclusions are drawn and possible future directions about slip boundary conditions for nanoscale fluid flow are prospected
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