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Simulating surfactant effects in phase-transforming fluids

Keyu Feng, Saikat Mukherjee, Tianyi Hu, Hector Gomez

TL;DR

The paper develops a thermodynamically consistent phase-field model based on the isothermal Navier-Stokes-Korteweg equations to simulate surfactant effects on liquid-vapor transformations. It introduces a reconstructed interfacial chemistry via a reconstructed chemical potential $\mu^{\text{rc}}(\rho,c)$, coupled to Langmuir adsorption, and decouples interface thickness from surfactant concentration using a diffuse-domain approach and $\lambda$-scaling. The model reproduces the observed SDS surface-tension trend up to the CMC, predicts interface oscillation frequencies consistent with theory, and captures surfactant-assisted deformation, inhibited coalescence, and delayed condensation in bubble populations. Overall, the framework provides a versatile, thermodynamically grounded tool for studying surfactant dynamics in non-equilibrium phase-change flows and points to future work on complex surface chemistries and acoustic responses.

Abstract

Surfactants are critical in natural processes and engineering, but measuring their concentrations in non-equilibrium conditions and in the presence of flow is difficult. Therefore, computational methods are a key tool for improving our understanding. Predicting the effect of surfactants on liquid-vapor transformations is particularly challenging due to (1) simultaneous mass transfer, non-equilibrium thermodynamics and Marangoni stresses, and (2) the phenomenological assumptions underlying many liquid-vapor phase-change models. Starting from the Navier-Stokes-Korteweg equations, a first-principles approach to liquid-vapor phase transformations, we developed a model of liquid-vapor flows with surfactants. We performed simulations of bubbles under equilibrium and liquid-vapor interface oscillations to demonstrate that the model successfully reproduces surfactant-mediated reductions in surface tension. We also investigated the mechanisms whereby surfactant affects bubble coalescence and condensation. Overall, this work provides a new framework for studying the effect of surfactants on liquid-vapor transformations and suggests multiple areas for future research, including the impact of complex surface chemistries on flow around bubbles and the acoustic response of bubbles with surfactants.

Simulating surfactant effects in phase-transforming fluids

TL;DR

The paper develops a thermodynamically consistent phase-field model based on the isothermal Navier-Stokes-Korteweg equations to simulate surfactant effects on liquid-vapor transformations. It introduces a reconstructed interfacial chemistry via a reconstructed chemical potential , coupled to Langmuir adsorption, and decouples interface thickness from surfactant concentration using a diffuse-domain approach and -scaling. The model reproduces the observed SDS surface-tension trend up to the CMC, predicts interface oscillation frequencies consistent with theory, and captures surfactant-assisted deformation, inhibited coalescence, and delayed condensation in bubble populations. Overall, the framework provides a versatile, thermodynamically grounded tool for studying surfactant dynamics in non-equilibrium phase-change flows and points to future work on complex surface chemistries and acoustic responses.

Abstract

Surfactants are critical in natural processes and engineering, but measuring their concentrations in non-equilibrium conditions and in the presence of flow is difficult. Therefore, computational methods are a key tool for improving our understanding. Predicting the effect of surfactants on liquid-vapor transformations is particularly challenging due to (1) simultaneous mass transfer, non-equilibrium thermodynamics and Marangoni stresses, and (2) the phenomenological assumptions underlying many liquid-vapor phase-change models. Starting from the Navier-Stokes-Korteweg equations, a first-principles approach to liquid-vapor phase transformations, we developed a model of liquid-vapor flows with surfactants. We performed simulations of bubbles under equilibrium and liquid-vapor interface oscillations to demonstrate that the model successfully reproduces surfactant-mediated reductions in surface tension. We also investigated the mechanisms whereby surfactant affects bubble coalescence and condensation. Overall, this work provides a new framework for studying the effect of surfactants on liquid-vapor transformations and suggests multiple areas for future research, including the impact of complex surface chemistries on flow around bubbles and the acoustic response of bubbles with surfactants.

Paper Structure

This paper contains 13 sections, 33 equations, 6 figures, 1 table.

Figures (6)

  • Figure 1: Original (black) and reconstructed (green) chemical potential in the interfacial region.
  • Figure 2: (A) Surface tension obtained from simulation (red line) and experiments (gray markers) Zhang2014-zp as a function of SDS concentration. (B) Spatial variation of the density for different values of the surfactant concentration, showing that the density profile does not change with surfactant concentration.
  • Figure 3: (A) Computational domain showing liquid water at the bottom and water vapor at the top. The initial interface has a sinusoidal shape. The red box highlights the region of interest, whose time evolution is shown on the right for different values of $c_l$. (B) Oscillation frequency of the interface as a function of surfactant concentration.
  • Figure 4: (A) Density contours at equilibrium, illustrating the deformation of a single bubble in shear flow. The bubble deforms into an elliptical shape, characterized by a major axis diameter $l$, a minor axis diameter $d$, and an angle of inclination $\beta$. (B) Contour of velocity magnitude. Color arrows are scaled by local velocity magnitude and indicate the flow direction. The black solid line represents the vapor-liquid interface.
  • Figure 5: (A) Top: time evolution of the inclination angle $\beta$ of the bubble in shear flow for different values of $c_l$; Bottom: Time evolution of $D$ for different values of $c_l$. (B) Comparison of $\beta$ (top) and $D$ (bottom) using theoretical estimates (dashed line) and simulation results (circular markers).
  • ...and 1 more figures