It is known that rapid mixing in microchannels overcomes the inherent diffusion-limited mixing of laminar flow. Consequently, many techniques that enhance microfluidic mixing are under development: slanted wells, shallow grooves, electrokinetic instability mixing and surface layers, etc. The long-term goal of this work is the optimization of surface-property distributions to control mixing and provide surface-directed flows. In this work, binary fluid mixing is explored using the lattice Boltzmann Method (LBM) to simulate flows in two-dimensional, microfluidic channels having surface temperature variations. Previous work has shown the advantages of controlled wall temperature distributions (i.e., flow-through PCR devices). Over 100 mixing scenarios were simulated by varying the Reynolds number, wall temperature distributions, binary fluid density ratios and interaction strengths, and the coupling strength between momentum and temperature. If one adds channel geometry variations, we are optimizing a mixing function over a multidimensional parameter space of large dimension. This vector-valued mixing function contains two scalar-valued objective functions. Each objective function measures the mixing obtained for fluid 1 and fluid 2. The optimization problem is to find designs that simultaneously attain an optimal mix of both fluids. Consequently, we have a massive, computationally-intensive, multiobjective optimization problem. In multiobjective optimization problems, many acceptable designs can be obtained by trading one objective function against the other. For example, one might accept a slightly worse mixing of fluid 1 for a much better mix of fluid 2. We demonstrate optimal mixing as a function of these designs, that is the variation of the wall temperatures and the heater lengths.
The concept of micro wall jets has been applied to the low Reynolds number (Re≤1), two-dimensional channel flows which may be found in biosensor microfluidic systems. The current numerical investigation utilizes the lattice Boltzmann method for flow field, temperature and binary fluid transport computations. Inlet and wall temperatures were specified along with various binary fluid properties to demonstrate their effect on the main channel flow due to the addition of micro wall jets. Results indicate similar levels of mixing for single and double jet configurations. The data also indicates the potential of using opposing jets to focus the binary fluid in the center of the channel.
It is known that rapid mixing in microchannels overcomes the inherent diffusion-limited mixing of laminar flow. Consequently, many techniques that enhance microfluidic mixing are under development: slanted wells, shallow grooves, electrokinetic instability mixing and surface layers, etc. The long-term goal of this work is the optimization of surface-property distributions to control mixing and provide surface-directed flows. In this work, binary fluid mixing is explored using the lattice Boltzmann Method (LBM) to simulate flows in two-dimensional, microfluidic channels having surface temperature variations. Previous work has shown the advantages of controlled wall temperature distributions (i.e., flow-through PCR devices). Over 100 mixing scenarios were simulated by varying the Reynolds number, wall temperature distributions, binary fluid density ratios and interaction strengths, and the coupling strength between momentum and temperature. If one adds channel geometry variations, we are optimizing a mixing function over a multidimensional parameter space of large dimension. This vector-valued mixing function contains two scalar-valued objective functions. Each objective function measures the mixing obtained for fluid 1 and fluid 2. The optimization problem is to find designs that simultaneously attain an optimal mix of both fluids. Consequently, we have a massive, computationally-intensive, multiobjective optimization problem. In multiobjective optimization problems, many acceptable designs can be obtained by trading one objective function against the other. For example, one might accept a slightly worse mixing of fluid 1 for a much better mix of fluid 2. We demonstrate optimal mixing as a function of these designs, that is the variation of the wall temperatures and the heater lengths.
It is known that rapid mixing in biosensors is required; however, these sensors may use reagents having small diffusion coefficients and whose mixing time scale is longer than the chemical reaction or molecular event time scale. Thus, it is necessary to overcome the inherent diffusion limited mixing of laminar flow. Many techniques to enhance microfluidic mixing are under development such as slanted wells, shallow grooves, electrokinetic instability mixing and surface layers. In this work, enhanced mixing is explored using lattice Boltzmann simulation techniques of two and three dimensional microfluidic channels at low Reynolds numbers. Surface temperature variations and flow field slip and no-slip boundary conditions emulating hydrophobic and hydrophilic surfaces were applied. The combined effect of wall temperature and surface property distributions presents a new way to manipulate microchannel flow fields. The momentum and thermal lattice Boltzmann equations were coupled via a body force term in the momentum equation. Also, a two dimensional, binary fluid model was incorporated. The results show how various wall temperature distributions, subjected to various velocity wall boundary conditions, can be either beneficial or counter productive to obtain uniform flow temperature profiles in, for example, PCR applications. The addition of the binary fluid model demonstrates the effects of both wall temperature and wall velocity boundary conditions.
The concept of macro scale synthetic jets has been applied to the low Reynolds number channel flows associated with biosensor microfluidics. The current numerical investigation utilizes a hybrid approach of the lattice Boltzmann method for flow field computations and the convection-diffusion equation for passive scalar transport. The study presents results for various synthetic jet geometries, jet inlet conditions, scaling issues and Reynolds numbers. The results indicate limited effects due to synthetic jet cavity-slot geometry and that the synthetic jet imparts momentum to the channel flow thus enhancing fluid mixing.
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