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Around a glass transition, the dynamics of a supercooled liquid dramatically slow down, exhibited by caging of particles, while the structural changes remain subtle. In alternative to recent machine learning studies searching for structural…

Disordered Systems and Neural Networks · Physics 2022-09-07 Kaihua Zhang , Xinyang Li , Yuliang Jin , Ying Jiang

We study concentrated colloidal suspensions, a model system which has a glass transition. Samples in the glassy state show aging, in that the motion of the colloidal particles slows as the sample ages from an initial state. We study the…

Soft Condensed Matter · Physics 2007-05-23 Gianguido C. Cianci , Rachel E. Courtland , Eric R. Weeks

We study the effect of physical aging on the mechanical properties of a model polymer glass using molecular dynamics simulations. The creep compliance is determined simultaneously with the structural relaxation under a constant uniaxial…

Soft Condensed Matter · Physics 2009-11-13 Mya Warren , Joerg Rottler

Structural defects control the kinetic, thermodynamic and mechanical properties of glasses. For instance, rare quantum tunneling two-level systems (TLS) govern the physics of glasses at very low temperature. Because of their extremely low…

Disordered Systems and Neural Networks · Physics 2023-07-19 Simone Ciarella , Dmytro Khomenko , Ludovic Berthier , Felix C. Mocanu , David R. Reichman , Camille Scalliet , Francesco Zamponi

Unraveling the structural factors influencing the dynamics of amorphous solids is crucial. While deep learning aids in navigating these complexities, transparency issues persist. Inspired by the successful application of prototype neural…

Soft Condensed Matter · Physics 2024-03-19 Xiao Jiang , Zean Tian , Kenli Li , Wangyu Hu

We use confocal microscopy to study the aging of a bidisperse colloidal glass near rough and smooth boundaries. Near smooth boundaries, the particles form layers, and particle motion is dramatically slower near the boundary as compared to…

Soft Condensed Matter · Physics 2017-12-14 Cong Cao , Xinru Huang , Connie B. Roth , Eric R. Weeks

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

Many modern-day applications require the development of new materials with specific properties. In particular, the design of new glass compositions is of great industrial interest. Current machine learning methods for learning the…

Computational Physics · Physics 2024-02-07 Gregor Maier , Jan Hamaekers , Dominik-Sergio Martilotti , Benedikt Ziebarth

Using a non-local Monte Carlo algorithm, we study the aging of a fragile glass, being able to follow it up to equilibibrium down to 0.89 Tmc (Tmc is the Mode-Coupling temperature) and up to unprecedentedly large waiting times at lower…

Disordered Systems and Neural Networks · Physics 2007-05-23 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Verrocchio

We study aging in a colloidal suspension consisting of micron-sized particles in a liquid. This system is made glassy by increasing the particle concentration. We observe samples composed of particles of two sizes, with a size ratio of…

Soft Condensed Matter · Physics 2008-10-02 Jennifer M. Lynch , Gianguido C. Cianci , Eric R. Weeks

A model is proposed that considers aging and rejuvenation in a soft glassy material as respectively a decrease and an increase in free energy. The aging term is weighted by inverse of characteristic relaxation time suggesting greater…

Soft Condensed Matter · Physics 2015-02-25 Yogesh M. Joshi

We study the out of equilibrium dynamics of several models exhibiting aging. We attempt at identifying various types of aging systems using a phase space point of view: we introduce a trial classification, based on the overlap between two…

Condensed Matter · Physics 2009-10-28 A. Barrat , R. Burioni , M. Mézard

We review the field of the glass transition, glassy dynamics and aging from a statistical mechanics perspective. We give a brief introduction to the subject and explain the main phenomenology encountered in glassy systems, with a particular…

Statistical Mechanics · Physics 2020-10-12 Francesco Arceri , François P. Landes , Ludovic Berthier , Giulio Biroli

Aging phenomena have been studied in very different materials like polymers, supercooled liquids or disordered orientational crystals. We recall here the main features of aging in spin glasses, and use this example of magnetic systems as a…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Hammann , E. Vincent , V. Dupuis , M. Alba , M. Ocio , J. -P. Bouchaud

Amorphous solids, or glasses, are distinguished from crystalline solids by their lack of long-range structural order. At the level of two-body structural correlations, glassformers show no qualitative change upon vitrifying from a…

Soft Condensed Matter · Physics 2015-06-11 C. Patrick Royall , Stephen R. Williams

Few questions in condensed matter science have proven as difficult to unravel as the interplay between structure and dynamics in supercooled liquids and glasses. The conundrum: close to the glass transition, the dynamics slow down…

We study the Metropolis dynamics of the simplest mean-field spin glass model, the Random Energy Model. We show that this dynamics exhibits aging by showing that the properly rescaled time change process between the Metropolis dynamics and a…

Probability · Mathematics 2015-02-17 Jiří Černý , Tobias Wassmer

Ageing of organic glasses to the equilibrium liquid state is studied by measuring the dielectric loss utilizing a microregulator where temperature is controlled by means of a Peltier element. Compared to conventional equipment the new…

Soft Condensed Matter · Physics 2011-07-18 Niels Boye Olsen , Tina Hecksher , Kristine Niss , Jeppe C. Dyre

Establishing reliable and interpretable structure-property relationships in glasses is a longstanding challenge in condensed matter physics. While modern data-driven machine learning techniques have proven highly effective in establishing…

Disordered Systems and Neural Networks · Physics 2026-02-06 Chenyan Wang , Mouyang Cheng , Ji Chen

Understanding glasses is considered to be one of the most fundamental problems in statistical physics. A theoretical approach to unravel their universal properties is to consider the validity of equilibrium concepts such as temperature and…

Soft Condensed Matter · Physics 2015-06-25 Ping Wang , Chaoming Song , Hernan A. Makse