Time Resolved Correlation measurements of temporally heterogeneous dynamics

TL;DR

This paper discusses an optimized method for Time Resolved Correlation (TRC) light scattering technique to detect and analyze dynamic heterogeneities in materials, including noise correction and application examples.

Contribution

It introduces a noise correction scheme for TRC measurements and demonstrates its effectiveness in analyzing heterogeneous dynamics.

Findings

Noise contribution affects fluctuation statistics in TRC.

A method for noise correction via N→∞ extrapolation is proposed.

Examples show improved detection of heterogeneous dynamics.

Abstract

Time Resolved Correlation (TRC) is a recently introduced light scattering technique that allows to detect and quantify dynamic heterogeneities. The technique is based on the analysis of the temporal evolution of the speckle pattern generated by the light scattered by a sample, which is quantified by $c\_I(t,\tau)$, the degree of correlation between speckle images recorded at time $t$ and $t+\tau$. Heterogeneous dynamics results in significant fluctuations of $c\_I(t,\tau)$ with time $t$. We describe how to optimize TRC measurements and how to detect and avoid possible artifacts. The statistical properties of the fluctuations of $c\_I$ are analyzed by studying their variance, probability distribution function, and time autocorrelation function. We show that these quantities are affected by a noise contribution due to the finite number $N$ of detected speckles. We propose and demonstrate a method to correct for the noise contribution, based on a $N\to \infty$ extrapolation scheme. Examples from both homogeneous and heterogeneous dynamics are provided. Connections with recent numerical and analytical works on heterogeneous glassy dynamics are briefly discussed.