Expanding the reach of diffusing wave spectroscopy and tracer bead microrheology

TL;DR

This paper advances diffusing wave spectroscopy (DWS) by developing a calibration-free data merging method, applying exponential basis fitting, and introducing inertia corrections, thereby enhancing microrheology measurements especially at high frequencies.

Contribution

It presents a novel calibration-free approach to merge DWS data, improves short-time data quality with exponential fitting, and introduces inertia corrections for better high-frequency microrheology.

Findings

Enhanced data merging technique for DWS.

Improved accuracy at short correlation times.

More reliable high-frequency microrheology measurements.

Abstract

Diffusing Wave Spectroscopy (DWS) is an extension of standard dynamic light scattering (DLS), applied to soft materials that are turbid or opaque. The propagation of light is modeled using light diffusion, characterized by a light diffusion coefficient that depends on the transport mean free path l* of the medium. DWS is highly sensitive to small particle displacements or other local fluctuations in the scattering properties and can probe sub-nanometer displacements. Analyzing the motion of beads in a viscoelastic matrix, known as one-bead microrheology, is one of the most common applications of DWS. Despite significant advancements since its invention in the late 1980s, including two-cell and multispeckle DWS, challenges such as merging single- and multispeckle data and limited accuracy for short correlation times persist. Here, we address these issues by improving the two-cell echo DWS scheme. We propose a calibration-free method to blend and merge echo and two-cell DWS data and demonstrate the use of an exponential basis fit to enhance data quality, in particular at very short times. Building on this, we introduce stable corrections for bead and fluid inertia, significantly improving the quality of microrheology data at high frequencies.