Interaction Potentials and Glass Formation: A Survey of Computer Experiments

Angell, C. Austen; Clarke, J. H. R.; Woodcock, Leslie V.

doi:10.1002/9780470142684.ch5

Cited by 212 publications

(24 citation statements)

References 98 publications

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“…Indeed, the splitting of the second maximum reflects a smearing of the probability distribution of atoms in the second coordination sphere and, hence, is reasonably attributed to the amorphization process. Moreover, a correlation between manifestations of the amorphous state and specific features in the range of the second maximum of the distribution function has been confirmed by real experiments on neutron and X-ray scattering [1,2].…”

Section: Introductionmentioning

confidence: 57%

“…Over the last three decades there have appeared, a number of works devoted to the numerical simulation of the glass transition in simple liquids with the use of the intermolecular interaction potential described by the Lennard-Jones equation [1][2][3][4][5][6]. One of the interesting results of these investigations is the splitting of the second maximum of the radial distribution function into two peaks at a particular temperature, which can be interpreted as the liquid-glass transition temperature.…”

Section: Introductionmentioning

confidence: 99%

“…In a number of works concerned with the numerical simulation [2][3][4], the point of transition from a liquid state to a vitreous states has been determined from the temperature dependence of the specific volume.…”

Section: Introductionmentioning

confidence: 99%

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Application of the molecular dynamics method and the excited state model to the investigation of the glass transition in argon

et al. 2006

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The glass transition in argon at a high cooling rate is simulated. At a temperature of 50 K (considerably below the melting temperature T f = 83.8 K), the fluctuation volume fraction reaches the constant value f g ≅ 0.03-0.05, which is close in the order of magnitude to the criterion for the glass transition in liquids f g ≈ const 0.02-0.03 within the excited state model. At this temperature, the second maximum of the radial distribution function is split as a result of the glass transition at the temperature T g ≈ 50 K. The approximate empirical "two-thirds" rule T g ≈ (2/3) T f is reasonably satisfied for argon. The data obtained are interpreted in the framework of the excited state model.

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Section: Introductionmentioning

confidence: 57%

Section: Introductionmentioning

confidence: 99%

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Application of the molecular dynamics method and the excited state model to the investigation of the glass transition in argon

et al. 2006

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“…By contrast, fast quenching processes, such as cooling molecular liquids or osmotically compressing dispersions of hard colloids, are known to produce nonequilibrium glassy states even if the components could, in principle, form highly ordered equilibrium high-density phases through slower processes (8)(9)(10)(11)(12)(13). For instance, hard spheres in three dimensions (3D) undergo a first-order crystallization disorderorder transition when slowly compressed, yet can also be forced into a disordered and arrested (i.e., nonergodic) glassy solid through a rapid quench in their volume fraction to a value that is near but below the point at which the spheres actually jam (4,(14)(15)(16)(17)(18). Other types of glasses can be formed through mechanisms such as attractive interactions or entanglements between constituent objects (1)(2)(3).…”

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confidence: 99%

Shape-designed frustration by local polymorphism in a near-equilibrium colloidal glass

Zhao

Mason

2015

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

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We show that hard, convex, lithographic, prismatic kite platelets, each having three 72°vertices and one 144°vertex, preferentially form a disordered and arrested 2D glass when concentrated quasistatically in a monolayer while experiencing thermal Brownian fluctuations. By contrast with 2D systems of other hard convex shapes, such as squares, rhombs, and pentagons, which readily form crystals at high densities, 72°kites retain a liquid-like disordered structure that becomes frozen-in as their long-time translational and rotational diffusion become highly bounded, yielding a 2D colloidal glass. This robust glass-forming propensity arises from competition between highly diverse few-particle local polymorphic configurations (LPCs) that have incommensurate features and symmetries. Thus, entropy maximization is consistent with the preservation of highly diverse LPCs en route to the arrested glass.A lthough much is known about many different kinds of glassy materials, including entangled polymers, dispersions of hard particles at high densities, and spin glasses (1-7), no single universal mechanism for glass formation describes them all. When isotropic Brownian systems of hard shapes are compressed slowly, the development of long-range order, typical of equilibrium crystal or liquid crystal phases, can either occur or be suppressed. By contrast, fast quenching processes, such as cooling molecular liquids or osmotically compressing dispersions of hard colloids, are known to produce nonequilibrium glassy states even if the components could, in principle, form highly ordered equilibrium high-density phases through slower processes (8-13). For instance, hard spheres in three dimensions (3D) undergo a first-order crystallization disorderorder transition when slowly compressed, yet can also be forced into a disordered and arrested (i.e., nonergodic) glassy solid through a rapid quench in their volume fraction to a value that is near but below the point at which the spheres actually jam (4, 14-18). Other types of glasses can be formed through mechanisms such as attractive interactions or entanglements between constituent objects (1-3). Disordered glasses differ from disordered gels, because gels result from strong attractions between constituents compared with thermal energy, and gels typically have much larger local spatial inhomogeneities than glasses (19). Thus, dispersions of colloidal particles that are not highly attractive and have hard interactions can be model glassy systems. Molecular and colloidal glass formers have been classified according to the notion of fragility (2, 20), which involves relative differences in attractive interactions. Nevertheless, a general theory of the glass-forming propensity of hard Brownian particles as a function of shape remains elusive. Moreover, dense glassy states typically have a significant residual entropy (21), reflecting orientational and positional randomness of constituent particles. The role of residual entropy in the general context of entropy maximization (22, 23) of hard...

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“…Some applications are found in modeling of ideal liquids [1,2], amorphous materials [3,4], granular media [5], emulsions [6], glasses [7], jamming [8], ceramic components [9,10] and densification processes during sintering [11,12]. The understanding of the final structure of the particles aggregation is important because its physical properties may depend on the packing features such as packing density, mean coordination number, porosity and radial distribution function (RDF).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation of Random Packing of Polydispersive Fine Particles

Ferraz

Marques

2017

Braz J Phys

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In this paper, we perform molecular dynamics (MD) simulations to study the two-dimensional packing process of both monosized and random size particles with radii ranging from 1.0 µm to 7.0 µm. The initial positions as well as the radii of five thousand fine particles were defined inside a retangular box by using a random number generator. Both the translational and the rotational movement of each particle were considered in the simulations. In order to deal with interacting fine particles, we take into account both the contact forces and the long-range dispersive forces. We account for normal and static/sliding tangential friction forces between particles and between particle and wall by means of a linear model approach, while the long-range dispersive forces are computed by using a Lennard-Jones like potential. The packing processes were studied assuming different long-range interaction strengths. We carry out statistical calculations of the different quantities studied such as packing density, mean coordination number, kinetic energy and radial distribution function as the system evolves over time. We find that the long-range dispersive forces can strongly influence the packing process dynamics as they might form large particle clusters, depending on the intensity of the long-range interaction strength.

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Interaction Potentials and Glass Formation: A Survey of Computer Experiments

Cited by 212 publications

References 98 publications

Application of the molecular dynamics method and the excited state model to the investigation of the glass transition in argon

Application of the molecular dynamics method and the excited state model to the investigation of the glass transition in argon

Shape-designed frustration by local polymorphism in a near-equilibrium colloidal glass

Dynamic Simulation of Random Packing of Polydispersive Fine Particles

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