


Multi Speckle-Diffusing Wave Spectroscopy
MS-DWS is the key light scattering method which measures the mobility of particles in a media.
HOW IT WORKS ?
DWS measures the fluctuation of the light intensity scattered by the sample. Light fluctuates because of the mobility of the particles (Brownian motion).

Interfering Backscattering wave generated by the motion of the particles leads to a speckle pattern formation on the multipixels detector.

Speckle image generated on the Multipixel detectors is treated to plot the decorrelation curve which quantifies the particle motion speed

Decorrelation curve enables to plot the particle Mean Square Displacement (MSD) which quantify the displacement in nanometer of the particles

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MSD curve enables to calculate the microrheology Viscous and Elastic moduli (G’’µR , G’µR) using the Generalized Stokes-Einstein Relation (GSER)

MAIN ADVANTAGES

MS-DWS and
Microrheology
Multi-speckle Diffusing Wave Spectroscopy micro-rheology (MS-DWS µRheology) is a recently introduced technique that greatly simplifies rheological measurements. No macroscopic deformation is applied to the sample. Instead, state-of-the-art optical techniques are used to measure the nanometer-scale motion of the sample constituents due to thermal energy. Rheological properties are deduced from this motion using a well-established formalism.
Advantages of MS-DWS µRheology include:
Luca Cipelletti
Professor
University of Montpellier
Institut Universitaire de France
Soft Material department
PARTICLES MOBILITY ANALYSIS
DWS is the Dynamic Light Scattering extended to opaque media.
DLS is well known to measure the particles Brownian motion in a diluted media in order to determine the particle size.
In a DWS experiment, light is scattered several times. This method enables to probe accurately the particle displacement to analyse the viscoelastic properties of complex fluids.
EXPERIMENT SET UP

Rheolaser™ range use the MS-DWS principle of measurement to accurately characterize the viscoelastic properties of soft materials.