Differential Variance Analysis: a direct method to quantify and visualize dynamic heterogeneities

Abstract

Many amorphous materials show spatially heterogenous dynamics, as different regions of the same system relax at different rates. Such a signature, known as Dynamic Heterogeneity, has been crucial to understand the nature of the jamming transition in simple model systems and is currently considered very promising to characterize more complex fluids of industrial and biological relevance. Unfortunately, measurements of dynamic heterogeneities typically require sophisticated experimental set-ups and are performed by few specialized groups. It is now possible to quantitatively characterize the relaxation process and the emergence of dynamic heterogeneities using a straightforward method, here validated on video microscopy data of hard-sphere colloidal glasses. We call this method Differential Variance Analysis (DVA), since it focuses on the variance of the differential frames, obtained subtracting images at different time-lags. Moreover, direct visualization of dynamic heterogeneities naturally appears in the differential frames, when the time-lag is set to the one corresponding to the maximum dynamic susceptibility. This approach opens the way to effectively characterize and tailor a wide variety of soft materials, from complex formulated products to biological tissues.

Emergence and percolation of rigid domains during the colloidal glass transition

“…Figure 2c plots the measured τ α , τ β and ∆t act in unjammed colloidal samples. The increase of the relaxation time is modest near the jamming point compared to standard hard sphere systems [42,43], due to the softness of PNIPAM spheres. Below φ = 0.69, ∆t act is short, and the τ α and τ β are close.…”

Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

“…In this respect, comparing real-space and Fourier-space techniques teaches an interesting lesson: while visualizing intermittent, collective motility events is easier in real-space, the calculation of the dynamic susceptibility is more immediate in the reciprocal space, where however no visual information is available. DDM may offer the needed intermediate perspective, and an important step in this direction has been recently made by Pastore et al with the introduction of Difference Variance Analysis (DVA) 57 . As in DDM, the key idea is that taking differences between images separated by a variable delay is a direct way of isolating only the contribution of moving entities in the sample.…”

The nature of collective excitations and their crossover at extreme supercritical conditions

“…In contrast, particle dynamics below the line have two components of motion: solid-like oscillatory motion and diffusive jump motion which enables the system to flow. This regime of particle dynamics below the FL is similar to that in low-temperature liquids, including the viscous liquids in the glass transformation range 16,17 .…”