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We present a novel thermodynamically guided, low-noise, time-scale bridging, and pertinently efficient strategy for the dynamic simulation of microscopic models for complex fluids. The systematic coarse-graining method is exemplified for…

Soft Condensed Matter · Physics 2010-11-12 Patrick Ilg , Hans Christian Öttinger , Martin Kröger

We report a molecular dynamics simulation study of the properties of the potential energy landscape sampled by a system of water molecules during the process of generating a glass by cooling, and during the process of regenerating the…

Soft Condensed Matter · Physics 2009-11-10 Nicolas Giovambattista , H. Eugene Stanley , Francesco Sciortino

We present a model for glassy dynamics in supercooled liquid mixtures. Given the relaxation behavior of individual supercooled liquids, the model predicts the relaxation times of their mixtures as temperature is decreased. The model is…

Statistical Mechanics · Physics 2019-09-11 Shachi Katira , Juan P. Garrahan , Kranthi K. Mandadapu

Notwithstanding decades of work, we still lack a satisfactory understanding of the structural relaxation that takes place as a liquid is rapidly cooled to form a glass. The present paper discusses a novel statistical characterization of…

Chemical Physics · Physics 2022-12-05 John Çamkıran , Fabian Parsch , Glenn D. Hibbard

The chemical potential of a component in a solution is defined as the free energy change as the amount of the component changes. Computing this fundamental thermodynamic property from atomistic simulations is notoriously difficult, because…

Statistical Mechanics · Physics 2022-10-12 Bingqing Cheng

The authors present a new molecular dynamics algorithm for sampling the isothermal-isobaric ensemble. In this approach the velocities of all particles and volume degrees of freedom are rescaled by a properly chosen random factor. The…

Statistical Mechanics · Physics 2009-03-10 Giovanni Bussi , Tatyana Zykova-Timan , Michele Parrinello

The scaling of the spatio-temporal response of coarsening systems is studied through simulations of the 2D and 3D Ising model with Glauber dynamics. The scaling functions agree with the prediction of local scale invariance, extending…

Statistical Mechanics · Physics 2016-08-31 Malte Henkel , Michel Pleimling

The variances of the fluid-particle acceleration and of the pressure-gradient and viscous force are given. The scaling parameters for these variances are velocity statistics measureable with a single-wire anemometer. For both high and low…

Fluid Dynamics · Physics 2019-06-19 Reginald J. Hill

We study the dynamics of particles in a multi-component 2d Lennard-Jones (LJ) fluid in the limiting case where {\it all the particles are different} (APD). The equilibrium properties of this APD system were studied in our earlier work…

Soft Condensed Matter · Physics 2016-06-22 Lenin S. Shagolsem , Yitzhak Rabin

In recent years lines along which structure and dynamics are invariant to a good approximation, so-called isomorphs, have been identified in the thermodynamic phase diagrams of several model liquids and solids. This paper reports computer…

Soft Condensed Matter · Physics 2022-04-14 Solvej Knudsen , B. D. Todd , Jeppe C. Dyre , J. S. Hansen

In this article we show that the phase-ordering scaling state for binary fluids is not necessarily unique and that local correlations in the initial conditions can be responsible for selecting the scaling state. We describe a new scaling…

Soft Condensed Matter · Physics 2007-05-23 A. J. Wagner

Using molecular dynamics simulations we examine the system size dependence of the fast dynamics in two model glass forming liquids, one of them a Lennard-Jones mixture for which cooperative fast relaxation has been reported. We find no…

Soft Condensed Matter · Physics 2018-10-17 D. Fragiadakis , C. M. Roland

On the basis of microscopic statistical mechanics of simple liquids the orientational interaction between clusters consisting of a particle and its nearest neighbors is estimated. It is shown that there are ranges of density and temperature…

Disordered Systems and Neural Networks · Physics 2009-11-10 N. M. Chtchelkatchev , V. N. Ryzhov , T. I. Schelkacheva , E. E. Tareyeva

In the quest to understand how structure and dynamics are connected in glasses, a number of machine learning based methods have been developed that predict dynamics in supercooled liquids. These methods include both increasingly complex…

Soft Condensed Matter · Physics 2022-06-08 Rinske M. Alkemade , Emanuele Boattini , Laura Filion , Frank Smallenburg

We have performed non-equilibrium dynamics simulations of a binary Lennard-Jones mixture in which an external force is applied on a single tagged particle. For the diffusive properties of this particle parallel to the force superdiffusive…

Statistical Mechanics · Physics 2015-06-11 Carsten F. E. Schroer , Andreas Heuer

Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solutions are tedious and require high computational power.…

Machine Learning · Computer Science 2024-02-21 Janny Steeven , Nadri Madiha , Digne Julie , Wolf Christian

A thermodynamically consistent particle-based model for fluid dynamics with continuous velocities and a non-ideal equation of state is presented. Excluded volume interactions are modeled by means of biased stochastic multiparticle…

Soft Condensed Matter · Physics 2009-11-11 Thomas Ihle , Erkan Tuzel , Daniel M. Kroll

Using extensive non-equilibrium molecular dynamics simulations, we investigate a glassforming binary Lennard-Jones mixture under shear. Both supercooled liquids and glasses are considered. Our focus is on the characterization of…

Soft Condensed Matter · Physics 2020-08-26 Mehrdad Golkia , Gaurav P. Shrivastav , Pinaki Chaudhuri , Jürgen Horbach

We use a standard Monte-Carlo algorithm to study the slow dynamics of a binary Lennard-Jones glass-forming mixture at low temperature. We find that Monte-Carlo is by far the most efficient way to simulate a stochastic dynamics since…

Statistical Mechanics · Physics 2015-06-25 Ludovic Berthier , Walter Kob

We use machine learning methods on local structure to identify flow defects - or regions susceptible to rearrangement - in jammed and glassy systems. We apply this method successfully to two disparate systems: a two dimensional experimental…

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