2017
DOI: 10.1103/physrevmaterials.1.073804
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Differential dynamic microscopy microrheology of soft materials: A tracking-free determination of the frequency-dependent loss and storage moduli

Abstract: Particle-tracking microrheology (PT-μr) exploits the thermal motion of embedded particles to probe the local mechanical properties of soft materials. Despite its appealing conceptual simplicity, PT-μr requires calibration procedures and operating assumptions that constitute a practical barrier to its wider application. Here we demonstrate differential dynamic microscopy microrheology (DDM-μr), a tracking-free approach based on the multiscale, temporal correlation study of the image intensity fluctuations that … Show more

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Cited by 49 publications
(66 citation statements)
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References 48 publications
(98 reference statements)
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“…DDM is a simple yet powerful tool to analyze time-lapse microscopy experiments and extract quantitative information about the structure and dynamics of a large class of microscope samples. As of today, DDM was applied successfully to a wide variety of physical and biological systems [7], including dilute isotropic [6,22] and anisotropic [23,24] colloidal particles, dense colloidal suspensions [12,25,26], molecular [27] and complex [28,29] fluids, motile microorganisms [12,30,31], sub-cellular structures [32,33], and microrheology [34,35]. DDM offers numerous advantages [9], such a simple implementation based on optical microscopes, low sensitivity to normal amounts of dirt or multiple scattering, and the possibility of using a variety of image-contrast mechanisms: bright field [6], dark-field [22], phase contrast [30], wide field fluorescence [36], polarized [24,29], differential interference contrast [32], light sheet [37], and confocal microscopy (ConDDM) [12,25,26,38].…”
Section: Differential Dynamic Microscopymentioning
confidence: 99%
“…DDM is a simple yet powerful tool to analyze time-lapse microscopy experiments and extract quantitative information about the structure and dynamics of a large class of microscope samples. As of today, DDM was applied successfully to a wide variety of physical and biological systems [7], including dilute isotropic [6,22] and anisotropic [23,24] colloidal particles, dense colloidal suspensions [12,25,26], molecular [27] and complex [28,29] fluids, motile microorganisms [12,30,31], sub-cellular structures [32,33], and microrheology [34,35]. DDM offers numerous advantages [9], such a simple implementation based on optical microscopes, low sensitivity to normal amounts of dirt or multiple scattering, and the possibility of using a variety of image-contrast mechanisms: bright field [6], dark-field [22], phase contrast [30], wide field fluorescence [36], polarized [24,29], differential interference contrast [32], light sheet [37], and confocal microscopy (ConDDM) [12,25,26,38].…”
Section: Differential Dynamic Microscopymentioning
confidence: 99%
“…24,25 For these reasons, DDM was recently introduced as a new method for performing microrheology on soft matter systems. [26][27][28] We complement the ensemble-averaged information obtained from DDM with single particle tracking, using the same time-lapse imaging data as input, in order to test for the presence of spatial and temporal heterogeneities in particle dynamics that typically arise in heterogeneous systems such as polymer gels. [29][30][31][32] In order to understand how the dynamics of hyaluronan networks are modulated by accessory extracellular molecules that introduce crosslinks, we probe singlecomponent gels with three different crosslink configurations: semidilute solutions, transiently crosslinked gels obtained by pH-triggered gelation, 33 and chemically crosslinked gels.…”
Section: Introductionmentioning
confidence: 99%
“…Different microrheological techniques, e.g. using differential dynamic microscopy (Cerbino and Trappe 2008;Edera et al 2017), diffusive wave spectroscopy (Pine et al 1988;Scheffold et al 2004), passive particle tracking (Mason et al 1997), or active microrheology (Keller et al 2001;Wintzenrieth et al 2014), have been developed and successfully applied. However, they are indirect and therefore require the extrapolation of bulk properties, which can be an issue for instance for heterogeneous systems.…”
Section: Introductionmentioning
confidence: 99%