The role of localization in glasses and supercooled liquids

Bembenek, Scott D.; Laird, Brian B.

doi:10.1063/1.471147

Cited by 86 publications

(62 citation statements)

References 35 publications

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“…Visual inspection suggests that these modes have a complex spatial structure, in which some groups of particles undergo cooperative motions, while others display incoherent displacements. While determining the precise nature of the modes in the GCM would While determining the precise nature of the modes in the GCM would require an analysis of N -dependence of the spectrum, and thus of the mobility edge [48], our analysis suggests that the giant dynamic heterogeneities of the GCM might indeed be associated to these extended unstable modes. In the KA mixture, instead, dynamic heterogeneities build up through dynamic facilitation of localized elementary rearrangements [16], which might be related to modes localized outside locally stable domains [47].…”

Section: Resultsmentioning

confidence: 97%

Mean-field dynamic criticality and geometric transition in the Gaussian core model

2016

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We use molecular dynamics simulations to investigate dynamic heterogeneities and the potential energy landscape of the Gaussian core model (GCM). Despite the nearly Gaussian statistics of particles' displacements, the GCM exhibits giant dynamic heterogeneities close to the dynamic transition temperature. The divergence of the four-point susceptibility is quantitatively well described by the inhomogeneous version of the Mode-Coupling theory. Furthermore, the potential energy landscape of the GCM is characterized by a geometric transition and large energy barriers, as expected from the lack of activated, hopping dynamics. These observations demonstrate that all major features of mean-field dynamic criticality can be observed in a physically sound, three-dimensional model.

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Section: Resultsmentioning

confidence: 97%

Mean-field dynamic criticality and geometric transition in the Gaussian core model

2016

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“…We shall denote these systems as SS 1 (36,41,42) and SS 2 (43,44). Finally, the Dzugutov potential (45) has been used (46-48), as well as a variety of other potentials (49)(50)(51)(52)(53)(54)(55). Simulations on models of molecular liquids, silica, and polymer melts have been performed, but they are beyond the scope of this review.…”

Section: Studies Of Supercooled Liquidsmentioning

confidence: 99%

Molecular dynamics studies of heterogeneous dynamics and dynamic crossover in supercooled atomic liquids

Andersen

2005

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

156

123

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Supercooled liquids near the glass transition exhibit the phenomenon of heterogeneous relaxation; at any specific time, a nominally homogeneous equilibrium fluid undergoes dynamic fluctuations in its structure on a molecular distance scale with rates that are very different in different regions of the sample. Several theoretical and simulation studies have suggested a change in the nature of the dynamics of fluids as they are supercooled, leading to the concept of a dynamic crossover that is often associated with mode coupling theory. Here, we will review the use of molecular dynamics computer simulation methods to investigate heterogeneous dynamics and dynamic crossovers in models of atomic liquids.glass transition ͉ mode coupling ͉ energy landscape M any studies of the dynamics of molecules in supercooled liquids at temperatures just above the glass transition have shown that in these systems the dynamics is heterogeneous. For recent reviews, see refs. 1-4.Several theoretical approaches suggest that at some temperature, which is usually below the freezing point, the characteristics of the dynamical motion on an atomic and molecular level change at a temperature often called a crossover temperature and often associated with the mode coupling theory (5-7).The two subjects of dynamic heterogeneity and dynamic crossover have many ramifications too numerous to discuss in the present review, and at first glance the connection between them is not apparent. In this article I will discuss the use of molecular dynamics (MD) computer simulations of liquids to study these two subjects, since many MD studies are directly relevant to both of the subjects. I will focus on a small number of model atomic liquids for which extensive calculations have been performed.

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“…The investigation makes use of the instantaneous normal-mode analysis (INM) 13 to determine the limit of stability of the algorithms by using the exact criterion for the stability of a discrete harmonic mode. Normal mode analysis has been very successful in investigations of viscous systems, [14][15][16][17] which is extremely time demanding to simulate and for which it is very important to optimize the MD simulations.…”

Section: Introductionmentioning

confidence: 99%

Stability of molecular dynamics simulations of classical systems

Toxværd

2012

The Journal of Chemical Physics

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The existence of a shadow HamiltonianH for discrete classical dynamics, obtained by an asymptotic expansion for a discrete symplectic algorithm, is employed to determine the limit of stability for molecular dynamics (MD) simulations with respect to the time-increment h of the discrete dynamics. The investigation is based on the stability of the shadow energy, obtained by including the first term in the asymptotic expansion, and on the exact solution of discrete dynamics for a single harmonic mode. The exact solution of discrete dynamics for a harmonic potential with frequency ω gives a criterion for the limit of stability h ≤ 2/ω. Simulations of the Lennard-Jones system and the viscous Kob-Andersen system show that one can use the limit of stability of the shadow energy or the stability criterion for a harmonic mode on the spectrum of instantaneous frequencies to determine the limit of stability of MD. The method is also used to investigate higher-order central difference algorithms, which are symplectic and also have shadow Hamiltonians, and for which one can also determine the exact criteria for the limit of stability of a single harmonic mode. A fourthorder central difference algorithm gives an improved stability with a factor of √ 3, but the overhead of computer time is a factor of at least two. The conclusion is that the second-order "Verlet"-algorithm, most commonly used in MD, is superior. It gives the exact dynamics within the limit of the asymptotic expansion and this limit can be estimated either from the conserved shadow energy or from the instantaneous spectrum of harmonic modes.

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The role of localization in glasses and supercooled liquids

Cited by 86 publications

References 35 publications

Mean-field dynamic criticality and geometric transition in the Gaussian core model

Mean-field dynamic criticality and geometric transition in the Gaussian core model

Molecular dynamics studies of heterogeneous dynamics and dynamic crossover in supercooled atomic liquids

Stability of molecular dynamics simulations of classical systems

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