Steady microfluidic measurements of mutual diffusion coefficients of liquid binary mixtures

Abstract

We present a microfluidic method leading to accurate measurements of the mutual diffusion coefficient of a liquid binary mixture over the whole solute concentration range in a single experiment. This method fully exploits solvent pervaporation through a poly(dimethylsiloxane) (PDMS) membrane to obtain a steady concentration gradient within a microfluidic channel. Our method is applicable for solutes which cannot permeate through PDMS, and requires the activity and the density over the full concentration range as input parameters. We demonstrate the accuracy of our methodology by measuring the mutual diffusion coefficient of the water (1) 1 glycerol (2) mixture, from measurements of the concentration gradient using Raman confocal spectroscopy and the pervaporation-induced flow using particle tracking velocimetry.The red line shows the theoretical velocity profile at z5h=2, the thick lines are the channel edges, and the dotted lines indicate the y-range of selected trajectories. (b) Corresponding evolutionx vs. t for the trajectories shown in (a). Linear fits (not shown for clarity) yield an estimate of the maximal velocity. [Color figure can be viewed at wileyonlinelibrary.com]

Buoyancy-driven dispersion in confined drying of liquid binary mixtures

“…a. Diffusive regime D1 -We define this regime as the one corresponding to ϕ 0 t ∼ ϕ 0 δ 2 in Eq. (33). Combining this relation with Eq.…”

“…Beyond the specific configuration investigated in the present work, different microfluidic tools have recently been developed to measure accurately the mutual diffusion coefficient of liquid mixtures owing to the very precise control of experimental conditions and mass transport at small scales [31][32][33]. In this context, Eq.…”

Generation of an O/W emulsion in a flow-focusing microchip: Importance of wetting conditions and of dynamic interfacial tension

“…Generally, there are three methods for solving wetting problems of the dispersed phase within microfluidic devices: surfactants addition (Tostado et al, 2011;Bashir et al, 2014;Yao et al, 2018); surface treatment (Li et al, 2007;Roberts et al, 2012;Li et al, 2018); and employment of non-planar geometry (Rotem et al, 2012;Jose and Cubaud, 2014;Yoon et al, 2018). The first two methods focus on increasing the equilibrium contact angles.…”

“…Therefore, an exploration about wetting behaviours with dibutyl adipate and n-butyl acetate within microfluidic devices is highly necessary. This exploration of wetting behaviours should also take into account previous works concerning the importance of the dynamic interfacial tension in microfluidic droplet generation (Tostado et al, 2011;Yao et al, 2018).…”

Prediction of Composition-Dependent Self-Diffusion Coefficients in Binary Liquid Mixtures: The Missing Link for Darken-Based Models

“…2,3 There is still a continuing demand for diffusion coefficients as input parameters to these models. 4 Although experimental methods are continuously improving, [5][6][7][8][9][10] the measurement of diffusion coefficients in liquids is usually time-consuming and expensive. 11,12 Molecular Dynamics (MD) simulations are a powerful tool to complement or even substitute diffusion experiments.…”