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The growth of correlation lengths in equilibrium glass-forming liquids near the glass transition is considered a critical finding in the quest to understand the physics of glass formation. These understandings helped us understand various…

Soft Condensed Matter · Physics 2023-08-16 Anoop Mutneja , Smarajit Karmakar

A unified treatment of structural relaxation in a deeply supercooled glassy liquid is developed which extends the existing mode coupling theory (MCT) by incorporating the effects of activated events by using the concepts from the random…

Disordered Systems and Neural Networks · Physics 2007-05-23 Sarika Maitra Bhattacharyya , Biman Bagchi , Peter G. Wolynes

A theory accounting for the dynamical aspects of the superfluid response of one dimensional (1D) quantum fluids is reported. In long 1D systems the onset of superfluidity is related to the dynamical suppression of quantum phase slips at low…

Statistical Mechanics · Physics 2012-02-13 Thomas Eggel , Miguel A. Cazalilla , Masaki Oshikawa

A recently introduced particle-based model for fluid dynamics with effective excluded volume interactions is analyzed in detail. The interactions are modeled by means of stochastic multiparticle collisions which are biased and depend on…

Soft Condensed Matter · Physics 2007-05-23 Thomas Ihle , Erkan Tuzel

We derive the Hydrodynamics for a system of N active, spherical, underdamped particles, interacting through conservative forces. At the microscopic level, we represent the evolution of the particles in terms of the Kramers equation for the…

Statistical Mechanics · Physics 2022-03-15 Umberto Marini Bettolo Marconi , Andrea Puglisi , Lorenzo Caprini

The quasistatic approximation is a useful but questionable simplification for analyzing step instabilities during the growth/evaporation of vicinal surfaces. Using this approximation, we characterized in Part I of this work the effect on…

Materials Science · Physics 2021-08-25 L. Guin , M. E. Jabbour , L. Shaabani-Ardali , N. Triantafyllidis

The complete quantitative description of the structure of dense and supercooled liquids remains a notoriously difficult problem in statistical physics. Most studies to date focus solely on two-body structural correlations, and only a…

Statistical Mechanics · Physics 2023-05-17 Ilian Pihlajamaa , Corentin C. L. Laudicina , Chengjie Luo , Liesbeth M. C. Janssen

The concept of fragility provides a possibility to rank different supercooled liquids on the basis of the temperature dependence of dynamic and/or thermodynamic quantities. We recall here the definitions of kinetic and thermodynamic…

Statistical Mechanics · Physics 2009-11-10 G. Ruocco , F. Sciortino , F. Zamponi , C. De Michele , T. Scopigno

There is growing evidence that slow dynamics and dynamic heterogeneity possess structural signatures in glass-forming liquids. However, even in the weakly frustrated glass-forming liquids, whether or not the dynamic heterogeneity has a…

Soft Condensed Matter · Physics 2015-06-11 Wen-Sheng Xu , Zhao-Yan Sun , Li-Jia An

We investigate the relaxation mechanism of a supercooled tetrahedral liquid at its limit of stability using isothermal isobaric ($NPT$) Monte Carlo (MC) simulations. In similarity with systems which are far from equilibrium but near the…

Statistical Mechanics · Physics 2017-09-06 Arvind Kumar Gautam , Nandlal Pingua , Aashish Goyal , Pankaj A. Apte

Elucidating the nature of the glass transition has been the holy grail of condensed matter physics and statistical mechanics for several decades. A phenomenological aspect that makes glass formation a conceptually formidable problem is that…

Soft Condensed Matter · Physics 2016-08-11 Shreyas Gokhale , K. Hima Nagamanasa , A. K. Sood , Rajesh Ganapathy

We show that facilitated spin mixtures with a tunable facilitation reproduce, on a Bethe lattice, the simplest higher-order singularity scenario predicted by the mode-coupling theory (MCT) of liquid-glass transition. Depending on the…

Disordered Systems and Neural Networks · Physics 2011-01-04 Mauro Sellitto , Daniele De Martino , Fabio Caccioli , Jeferson J. Arenzon

Numerically simulating deformations in thin elastic sheets is a challenging problem in computational mechanics due to destabilizing compressive stresses that result in wrinkling. Determining the location, structure, and evolution of…

Materials Science · Physics 2014-11-26 Michael Taylor , Benny Davidovitch , Zhanlong Qiu , Katia Bertoldi

We combine the hyper-netted chain approximation of liquid state theory with the mode-coupling theory of the glass transition to analyze the structure and dynamics of soft spheres interacting via harmonic repulsion. We determine the locus of…

Statistical Mechanics · Physics 2010-03-29 Ludovic Berthier , Elijah Flenner , Hugo Jacquin , Grzegorz Szamel

We study a spontaneous relaxation dynamics of arbitrarily shaped liquid drops on solid surfaces in the partial wetting regime. It is assumed that the energy dissipated near the contact line is much larger than that in the bulk of the fluid.…

Fluid Dynamics · Physics 2016-01-27 S. Iliev , N. Pesheva , Vadim Nikolayev

We consider the gravity-driven flow of a perfect dielectric, viscous, thin liquid film, wetting a flat substrate inclined at a non-zero angle to the horizontal. The dynamics of the thin film is influenced by an electric field which is set…

Fluid Dynamics · Physics 2019-08-30 Ruben J Tomlin , Radu Cimpeanu , Demetrios T Papageorgiou

We present a microscopic derivation of the laws of continuum mechanics of nonideal ordered solids including dissipation, defect diffusion, and heat transport. Starting point is the classical many-body Hamiltonian. The approach relies on the…

Statistical Mechanics · Physics 2022-11-23 Florian Miserez , Saswati Ganguly , Rudolf Haussmann , Matthias Fuchs

The existence of heterogeneity in the dynamics of supercooled liquids is believed to be one of the hallmarks of the glass transition. Intense research has been carried out in the past to understand the origin of this heterogeneity in…

Soft Condensed Matter · Physics 2020-07-01 Indrajit Tah , Smarajit Karmakar

Despite the striking successes of deep neural networks trained with gradient-based optimization, these methods differ fundamentally from their biological counterparts. This gap raises key questions about how nature achieves robust,…

Machine Learning · Computer Science 2025-10-15 Mattia Scardecchia

In this work we study the dynamic behaviour of compound shells of revolution partially filled with an ideal incompressible fluid based on boundary-value problems. New analytical mathematical model with corresponding discrete scheme for the…

Computational Engineering, Finance, and Science · Computer Science 2016-06-15 Iryna Kononenko , Oleksiy Kononenko
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