Flow of gaseous mixtures through rectangular microchannels driven by pressure, temperature, and concentration gradients

• Published in: Physics of fluids (1994) Vol. 17; no. 10; pp. 100607.1 - 100607.12
• Main Authors: Naris, S., Valougeorgis, D., Kalempa, D., Sharipov, F.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville, NY American Institute of Physics 01.10.2005
• Subjects: Applied fluid mechanics; Applied sciences; Electronics; Exact sciences and technology; Fluid dynamics; Fluidics; Free molecular flows; Fundamental areas of phenomenology (including applications); Micro- and nanoelectromechanical devices (mems/nems); Physics; Rarefied gas dynamics; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices; Rectangular pipe; Rarefied gas flow; Digital simulation; Free molecular flow; Binary mixtures; Microelectromechanical device; Microfluidics; Fluidics; Gas mixtures
• ISSN: 1070-6631; 1089-7666
• DOI: 10.1063/1.1896986

The flow of binary gaseous mixtures through rectangular microchannels due to small pressure, temperature, and molar concentration gradients over the whole range of the Knudsen number is studied. The solution is based on a mesoscale approach, formally described by two coupled kinetic equations, subject to diffuse scattering boundary conditions. The model proposed by McCormack substitutes the complicated collision term and the resulting kinetic equations are solved by an accelerated version of the discrete velocity method. Typical results are presented for the flow rates and the heat fluxes of two different binary mixtures (Ne–Ar and He–Xe) with various molar concentrations, in two-dimensional microchannels of different aspect (height to width) ratios. The formulation is very efficient and can be used instead of the classical method of solving the Navier–Stokes equations with slip boundary conditions, which is restricted by the hydrodynamic regime. Moreover, the present formulation is a good alternative to the direct simulation Monte Carlo method, which often becomes computationally inefficient.