C 60 : The First One-Component Gel?

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The behaviour of materials under spatial confinement is sensitively dependent on the nature of the confining boundaries. In two dimensions, confinement within a hard circular boundary inhibits the hexagonal ordering observed in bulk systems at high density. Using colloidal experiments and Monte Carlo simulations, we investigate two model systems of quasi hard discs under circularly symmetric confinement. The first system employs an adaptive circular boundary, defined experimentally using holographic optical tweezers. We show that deformation of this boundary allows, and indeed is required for, hexagonal ordering in the confined system. The second system employs a circularly symmetric optical potential to confine particles without a physical boundary. We show that, in the absence of a curved wall, near perfect hexagonal ordering is possible. We propose that the degree to which hexagonal ordering is suppressed by a curved boundary is determined by the "strictness" of that wall.

Section: The Colloidal Corralmentioning

confidence: 99%

The effect of boundary adaptivity on hexagonal ordering and bistability in circularly confined quasi hard discs

Williams¹,

Oğuz

Jack

et al. 2014

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“…27,[34][35][36][37][38][39] More recent studies, in line with our own work, 15 have considered more diverse systems, such as the phase separation kinetics of a coarse-grained model for buckyball C 60 carbon molecules. 40 Moreover, bicontinuous disordered structures reminiscent of the ones obtained in spinodal decompositions may also be found in colorful bird feathers, and were recently interpreted as incompletely phase separated polymeric glasses, 41,42 thus demonstrating the broad relevance of the problem of the glass-gas phase separation. Finally, even more complex mixtures that are relevant to food processing 43 or solar cell technology [44][45][46] also exhibit kinetically arrested spinodal decompositions, that might result from the fact that one component becomes mechanically rigid.…”

Section: Introductionmentioning

confidence: 98%

Intermittent dynamics and logarithmic domain growth during the spinodal decomposition of a glass-forming liquid

Testard

Berthier

Kob

2014

149

We use large-scale molecular dynamics simulations of a simple glass-forming system to investigate how its liquid-gas phase separation kinetics depends on temperature. A shallow quench leads to a fully demixed liquid-gas system whereas a deep quench makes the dense phase undergo a glass transition and become an amorphous solid. This glass has a gel-like bicontinuous structure that evolves very slowly with time and becomes fully arrested in the limit where thermal fluctuations become negligible. We show that the phase separation kinetics changes qualitatively with temperature, the microscopic dynamics evolving from a surface tension-driven diffusive motion at high temperature to a strongly intermittent, heterogeneous, and thermally activated dynamics at low temperature, with a logarithmically slow growth of the typical domain size. These results elucidate the microscopic mechanisms underlying a specific class of viscoelastic phase separation.

“…33 Here we describe a recent addition to the collection of high-order structural detection algorithms, the topological cluster classification (TCC) algorithm. This algorithm has been used to investigate higher-order structure in colloidal 32,34 and molecular 35 gels, colloid-polymer mixtures, 36 colloidal clusters, [37][38][39] simple liquids, 60 liquidvapor interfaces, 40 supercooled liquids, [41][42][43] and crystallising fluids. 44 The method shares some characteristics with other topological methods (e.g., the VFA and CNA methods).…”

Section: Introductionmentioning

confidence: 99%

Identification of structure in condensed matter with the topological cluster classification

Malins¹,

Williams²,

Eggers³

et al. 2013

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136

197

We describe the topological cluster classification (TCC) algorithm. The TCC detects local structures with bond topologies similar to isolated clusters which minimise the potential energy for a number of monatomic and binary simple liquids with m ≤ 13 particles. We detail a modified Voronoi bond detection method that optimizes the cluster detection. The method to identify each cluster is outlined, and a test example of Lennard-Jones liquid and crystal phases is considered and critically examined.