Measurement of the Four-Point Susceptibility of an Out-of-Equilibrium Colloidal Solution of Nanoparticles Using Time-Resolved Light Scattering

Maggi, Claudio; Leonardo, R. Di; Ruocco, G.; Dyre, Jeppe C.

doi:10.1103/physrevlett.109.097401

Cited by 10 publications

(18 citation statements)

References 26 publications

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“…41,42 Numerical simulations were instrumental for these studies since one can track the positions of all particles as a function of time and, hence, potentially measure all kinds of observables. The situation is different in experiments, where measuring four point functions is instead much more challenging; direct measurements of χ 4 have been obtained for granular systems 25,26 and colloids, 161,162 but not yet for molecular liquids. In consequence, alternative methods to probe the number of correlated molecules N corr have been developed.…”

Section: B Dynamical Correlationsmentioning

confidence: 99%

Perspective: The glass transition

Biroli

Garrahan

2013

The Journal of Chemical Physics

360

353

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We provide here a brief perspective on the glass transition field. It is an assessment, written from the point of view of theory, of where the field is and where it seems to be heading. We first give an overview of the main phenomenological characteristics, or "stylised facts," of the glass transition problem, i.e., the central observations that a theory of the physics of glass formation should aim to explain in a unified manner. We describe recent developments, with a particular focus on real space properties, including dynamical heterogeneity and facilitation, the search for underlying spatial or structural correlations, and the relation between the thermal glass transition and athermal jamming. We then discuss briefly how competing theories of the glass transition have adapted and evolved to account for such real space issues. We consider in detail two conceptual and methodological approaches put forward recently, that aim to access the fundamental critical phenomenon underlying the glass transition, be it thermodynamic or dynamic in origin, by means of biasing of ensembles, of configurations in the thermodynamic case, or of trajectories in the dynamic case. We end with a short outlook.

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Section: B Dynamical Correlationsmentioning

confidence: 99%

Perspective: The glass transition

Biroli

Garrahan

2013

The Journal of Chemical Physics

360

353

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“…One encounters numerical studies for both Ising [13,16,18] and Heisenberg [21,22] spin glasses, as well as for structural glasses [23][24][25][26][27]. On the experimental side, we have studies on atomic spin glasses [17,19], superspin glasses [10], polymers [9,28], colloids [29][30][31][32][33][34][35] or DNA [36].Here, we perform a detailed simulation of GFDR in the three-dimensional Ising spin glass employing the custommade supercomputers Janus [37] and Janus II [38]. In fact, this has been the launching simulation campaign of the Janus II machine, which was designed with this sort of dynamical studies in mind.…”

mentioning

confidence: 99%

“…We thus think that it should be possible to extract the spin-glass functional order parameter from already existing experimental data. Furthermore, GFDR have been studied as well in superspin glasses [10] and in a variety of soft condensed-matter systems [9,[28][29][30][31][32][33][34][35][36]. We therefore expect that our analysis will be of interest beyond the realm of spin glasses.Acknowledgments -Some of the simulations in this work (the L < 80 systems, to check for size effects) where carried out on the Memento cluster: we thank staff from BIFI's supercomputing center for their assistance.…”

mentioning

confidence: 99%

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

Baity‐Jesi

Calore

Cruz

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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We have performed a very accurate computation of the nonequilibrium fluctuation-dissipation ratio for the 3D Edwards-Anderson Ising spin glass, by means of large-scale simulations on the specialpurpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes.spin glasses | fluctuation-dissipation relation | glasses | statics-dynamics equivalence | out-of-equilibrium dynamics T heory and experiment follow apparently diverging paths when studying the glass transition. On the one hand, experimental glass formers (spin glasses, fragile molecular glasses, polymers, colloids, and . . .) undergo a dramatic increase of characteristic times when cooled down to their glass temperature, Tg (1). Below Tg, the glass is always out of equilibrium and "aging" appears (2). Consider a rapid quench from a high temperature to the working temperature T (T < Tg), where the system is left to equilibrate for time tw and probed at a later time t + tw. Response functions such as the magnetic susceptibility turn out to depend on t/t µ w , with µ ≈ 1 (2-4). The age of the glass, tw, remains the relevant time scale even for tw as large as several days. Relating the aging experimental responses to equilibrium properties is an open problem.A promising way to fill the gap is to establish a statics-dynamics dictionary (SDD) (5-8): nonequilibrium properties at "finite times" t, tw, as obtained on samples of macroscopic size L → ∞, are quantitatively matched to equilibrium quantities computed on systems of "finite size" L [the SDD is an L ↔ (t, tw) correspondence]. Clearly, in order for it to be of any value, an SDD cannot strongly depend on the particular pair of aging and equilibrium quantities that are matched.Some time ago, we proposed one such a SDD (6-8). However, this SDD was unsatisfactory in two respects. First, L was matched only to tw (irrespectively of the probing time t + tw). Second, our SDD matched spatial correlation functions whose experimental study is only incipient (9, 10).One could think (5) of building an SDD through the generalized fluctuation-dissipation relations (GFDRs) first introduced in ref. 11 (for related developments, see refs. 12-19). The GFDRs are correct at very large times. However, on time scales that can be investigated in experiments, glassy systems are not fully thermalized because the approach to equilibrium is very slow. Strong corrections pollute GFDRs at finite times. SignificanceThe unifying feature of glass formers (such as polymers, supercooled liquids, colloids, granulars, spin glasses, superconductors, etc.) is a sluggish dynamics at low temperatures. Indeed, their dynamics are so slow that thermal equilibrium is n...

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“…Moreover, particle tracking relies on quite complex algorithms and suffers possible biases due to users’ choice of tracking parameters. By contrast, Dynamic Light Scattering (DLS) based techniques are probably the most robust approach to measure χ 4 2324, but do not provide any direct visualization of DHs. Simultaneous visualization and quantitative measurement of DHs have been obtained using more sophisticated techniques, such as the Photon Correlation Imaging (PCI), that combines features of both dynamic light scattering and imaging25.…”

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confidence: 99%

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

Pastore

Pesce

Caggioni

2017

Sci Rep

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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.

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Measurement of the Four-Point Susceptibility of an Out-of-Equilibrium Colloidal Solution of Nanoparticles Using Time-Resolved Light Scattering

Cited by 10 publications

References 26 publications

Perspective: The glass transition

Perspective: The glass transition

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

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

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