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Computer simulations give precious insight into the microscopic behavior of disordered and amorphous materials, but their typical time scales are orders of magnitude shorter than the experimentally relevant ones. In particular, simulations of supercooled liquids cover at most 4-5 decades of viscous slowing down, which falls far short of the 13 decades commonly accessible in experimental studies. We close this enormous gap for a class of realistic models of liquids, which we successfully equilibrate beyond laboratory time scales by means of the swap Monte Carlo algorithm. We show that combined optimization of selected features of the interaction potential, such as particle softness, polydispersity and non-additivity, leads to computer models with excellent glass-forming ability. For such models, we achieve over 10 orders of magnitude speedup in equilibration time scale. This numerical advance allows us to address some outstanding questions concerning glass formation, such as the role of local structure and the relevance of an entropy crisis, in a dynamical range that remains inaccessible in experiments. Our results support the view that non-trivial static correlations continue to build up steadily in supercooled liquids even below the laboratory glass temperature.

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Ref Arxiv: 1701.00936
DOI: 10.1103/PhysRevE.95.052125
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We numerically analyse the density field of three-dimensional randomly jammed packings of monodisperse soft frictionles spherical particles, paying special attention to fluctuations occurring at large lengthscales. We study in detail the two-point static structure factor at low wavevectors in Fourier space. We also analyse the nature of the density field in real space by studying the large-distance behavior of the two-point pair correlation function, of density fluctuations in subsystems of increasing sizes, and of the direct correlation function. We show that such real space analysis can be greatly improved by introducing a coarse-grained density field to disentangle genuine large-scale correlations from purely local effects. Our results confirm that both Fourier and real space signatures of vanishing density fluctuations at large scale are absent, indicating that randomly jammed packings are not hyperuniform. In addition, we establish that the pair correlation function displays a surprisingly complex structure at large distances, which is however not compatible with the long-range negative correlation of hyperuniform systems but fully compatible with an analytic form for the structure factor. This implies that the direct correlation function is short-ranged, as we also demonstrate directly. Our results reveal that density fluctuations in jammed packings do not follow the behavior expected for random hyperuniform materials, but display instead a more complex behavior.

Commentaires: 11 pages, 9 figs. Réf Journal: Phys. Rev. E 95, 052125 (2017)

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Ref Arxiv: 1704.08864
DOI: 10.1103/PhysRevX.7.021039
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102 Citations
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Successful computer studies of glass-forming materials need to overcome both the natural tendency to structural ordering and the dramatic increase of relaxation times at low temperatures. We present a comprehensive analysis of eleven glass-forming models to demonstrate that both challenges can be efficiently tackled using carefully designed models of size polydisperse supercooled liquids together with an efficient Monte Carlo algorithm where translational particle displacements are complemented by swaps of particle pairs. We study a broad range of size polydispersities, using both discrete and continuous mixtures, and we systematically investigate the role of particle softness, attractivity and non-additivity of the interactions. Each system is characterized by its robustness against structural ordering and by the efficiency of the swap Monte Carlo algorithm. We show that the combined optimisation of the potential's softness, polydispersity and non-additivity leads to novel computer models with excellent glass-forming ability. For such models, we achieve over ten orders of magnitude gain in the equilibration timescale using the swap Monte Carlo algorithm, thus paving the way to computational studies of static and thermodynamic properties under experimental conditions. In addition, we provide microscopic insights into the performance of the swap algorithm which should help optimizing models and algorithms even further.

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Ref Arxiv: 1609.07979
DOI: 10.1063/1.4972525
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Classical particle systems characterized by continuous size polydispersity, such as colloidal materials, are not straightforwardly described using statistical mechanics, since fundamental issues may arise from particle distinguishability. Because the mixing entropy in such systems is divergent in the thermodynamic limit we show that the configurational entropy estimated from standard computational approaches to characterize glassy states also diverges. This reasoning would suggest that polydisperse materials cannot undergo a glass transition, in contradiction to experiments. We explain that this argument stems from the confusion between configurations in phase space and states defined by free energy minima, and propose a simple method to compute a finite and physically meaningful configurational entropy in continuously polydisperse systems. Physically, the proposed approach relies on an effective description of the system as an $M^*$-component system with a finite $M^*$, for which finite mixing and configurational entropies are obtained. We show how to directly determine $M^*$ from computer simulations in a range of glass-forming models with different size polydispersities, characterized by hard and soft interparticle interactions, and by additive and non-additive interactions. Our approach provides consistent results in all cases and demonstrates that the configurational entropy of polydisperse system exists, is finite, and can be quantitatively estimated.

Commentaires: 13 pages, 4 figures. v2: Published version. Réf Journal: J. Chem. Phys. 146, 014502 (2017)

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Collective motion in dense activematerials

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Facets of glass physics

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Melting of stable glasses