We report here an overview of current trends and a selection of recent results regarding the characterization of emulsions by Diffusing Wave Spectroscopy (DWS). We provide a synopsis of the state of the art of the DWS technique, and a critical discussion of experiments performed on samples in which Brownian and ballistic dynamics coexist. A novel analysis scheme is introduced for DWS experiments on creaming or sedimenting emulsions, allowing to extract not only average values for drop size and drop dynamics - as usual in DWS - but also properties related to the width of the distributions governing these quantities. This analysis scheme starts from a realistic Monte Carlo simulation of light diffusing in the volume of the sample and reaching the detector. This simulation is more accurate than the analytical expressions available for the idealized geometries normally used in DWS interpretation. By disentangling Brownian and ballistic motions we directly access the variance of velocity distribution, ?v. In relatively unstable emulsions ?v governs the frequency of drop-drop collisions and subsequent coalescence events. Furthermore, when gravity dominates dynamics, as in emulsions subject to sedimentation or creaming, ?v is strongly related to the 2nd and 4th moments of drop size distribution. This novel analysis scheme is exemplified investigating freshly formed model emulsions. Results are validated by comparison with microscopy imaging. This analysis is then extended to emulsions with a much broader drop size distribution, resembling those that are planned to be investigated in microgravity by the Soft Matter Dynamics facility onboard the International Space Station (ISS). This review is concluded by sketching some promising directions, and suggesting useful complementarities between DWS and other techniques, for the characterization of transient regimes in emulsions, and of destabilization processes of great practical importance.
Recent developments in emulsion characterization: Diffusing Wave Spectroscopy beyond average values
Liggieri L;Ravera F;Cristofolini L
2021
Abstract
We report here an overview of current trends and a selection of recent results regarding the characterization of emulsions by Diffusing Wave Spectroscopy (DWS). We provide a synopsis of the state of the art of the DWS technique, and a critical discussion of experiments performed on samples in which Brownian and ballistic dynamics coexist. A novel analysis scheme is introduced for DWS experiments on creaming or sedimenting emulsions, allowing to extract not only average values for drop size and drop dynamics - as usual in DWS - but also properties related to the width of the distributions governing these quantities. This analysis scheme starts from a realistic Monte Carlo simulation of light diffusing in the volume of the sample and reaching the detector. This simulation is more accurate than the analytical expressions available for the idealized geometries normally used in DWS interpretation. By disentangling Brownian and ballistic motions we directly access the variance of velocity distribution, ?v. In relatively unstable emulsions ?v governs the frequency of drop-drop collisions and subsequent coalescence events. Furthermore, when gravity dominates dynamics, as in emulsions subject to sedimentation or creaming, ?v is strongly related to the 2nd and 4th moments of drop size distribution. This novel analysis scheme is exemplified investigating freshly formed model emulsions. Results are validated by comparison with microscopy imaging. This analysis is then extended to emulsions with a much broader drop size distribution, resembling those that are planned to be investigated in microgravity by the Soft Matter Dynamics facility onboard the International Space Station (ISS). This review is concluded by sketching some promising directions, and suggesting useful complementarities between DWS and other techniques, for the characterization of transient regimes in emulsions, and of destabilization processes of great practical importance.File | Dimensione | Formato | |
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