Recent developments in emulsion characterization: Diffusing Wave Spectroscopy beyond average values

Spectral Properties of Foams and Emulsions

“…A new model for fitting DWS measurements of emulsions during their creaming/ sedimentation is presented in [177]. This model starts from a Monte Carlo simulation of the light that diffuses in the volume of the emulsion in order to determine the averages and the distributions of the droplet size and dynamics.…”

Deconvoluting Emulsion Stabilization Mechanisms Using Diffusing Wave Spectroscopy

“…The method was first described by Fahimi et al studying suspensions in a similar setup to the one employed in this work . The method was further adapted for the study of emulsions by Lorusso et al, and both a Brownian component and shear component were determined from the mean squared displacement of the emulsion droplets . In this work, a similar methodology of l * determination is utilized that builds on both of these prior works and is discussed in detail in McMillin et al This developed framework advances prior work by allowing for l *, extracted from a series of DWS experiments, to be connected with kinetics, providing unparalleled mechanistic information associated with destabilization in semisolid lubricating oil formulations.…”

“…18 The method was further adapted for the study of emulsions by Lorusso et al, and both a Brownian component and shear component were determined from the mean squared displacement of the emulsion droplets. 19 In this work, a similar methodology of l* determination is utilized that builds on both of these prior works and is discussed in detail in McMillin et al 15 This developed framework advances prior work by allowing for l*, extracted from a series of DWS experiments, to be connected with kinetics, providing unparalleled mechanistic information associated with destabilization in semisolid lubricating oil formulations. Furthermore, it is shown that l* may be used as a proxy for surface activity of specific additives, and dynamics may be determined by parametrization of mean squared displacement (MSD) bereft of a specific model.…”

“…Both s and P ( s ) are functions of the experimental geometry as well as l *, and in certain circumstances have an analytical form . However, if no analytical form can be constructed, the path length and path length distribution can be obtained via numerical Monte Carlo simulations specific to the geometry employed for a given value of l *. ,, For the experimental setup used in this work, Monte Carlo simulations were performed, as outlined in McMillin et al…”

“…Often, this is a result of body forces, such as gravity, acting on emulsions with a density contrast between the dispersed and continuous phases. When analyzing the mean squared displacement extracted from eq , it should be noted that superlinearity results from a variance in velocity and not velocity itself. , Subdiffusive motion implies that droplets move slower than diffusion and arises due to droplet–droplet interactions or gravitational compaction. In this regime, the mean squared displacement scales sublinearly in time.…”