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We show that the various crossovers between dynamical regimes observed in experiments and simulations of supercooled liquids can be explained in simple terms from the existence and statistical properties of dynamical heterogeneities. We…

Statistical Mechanics · Physics 2009-11-10 Ludovic Berthier , Juan P. Garrahan

The Arrhenius crossover temperature, $T_{A}$, corresponds to a thermodynamic state wherein the atomistic dynamics of a liquid becomes heterogeneous and cooperative; and the activation barrier of diffusion dynamics becomes…

Materials Science · Physics 2023-01-31 Bulat N. Galimzyanov , Maria A. Doronina , Anatolii V. Mokshin

We review the Random First Order Transition Theory of the glass transition, emphasizing the experimental tests of the theory. Many distinct phenomena are quantitatively predicted or explained by the theory, both above and below the glass…

Disordered Systems and Neural Networks · Physics 2015-06-25 Vassiliy Lubchenko , P. G. Wolynes

A molecular theory of the glass transition of network forming liquids is developed using a combination of self-consistent phonon and liquid state approaches. Both the dynamical transition and the entropy crisis characteristic of random…

Condensed Matter · Physics 2009-11-07 Randall W. Hall , Peter G. Wolynes

It has been a long-standing materials science challenge to establish structure-property relations in amorphous solids. Here we introduce a rotation-variant local structure representation that enables different predictions for different…

Materials Science · Physics 2022-03-15 Zhao Fan , Evan Ma

Precise and reliable climate projections are required for climate adaptation and mitigation, but Earth system models still exhibit great uncertainties. Several approaches have been developed to reduce the spread of climate projections and…

Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge when studying the glass transition. The absence of clear visible structural order in amorphous…

We investigate the heterogeneous dynamics in a model, where chemical gelation and glass transition interplay, focusing on the dynamical susceptibility. Two independent mechanisms give raise to the correlations, which are manifested in the…

Soft Condensed Matter · Physics 2017-05-09 Antonio de Candia , Annalisa Fierro , Raffaele Pastore , Massimo Pica Ciamarra , Antonio Coniglio

Using density-functional molecular dynamics simulations we analyzed the cooling-rate effects on the physical properties of GeS$_2$ chalcogenide glasses. Liquid samples were cooled linearly in time according to $T(t) = T_0 - \gamma t$ where…

Disordered Systems and Neural Networks · Physics 2007-05-23 Sebastien Le Roux , Philippe Jund

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

Swap algorithms can shift the glass transition to lower temperatures, a recent unexplained observation constraining the nature of this phenomenon. Here we show that swap dynamic is governed by an effective potential describing both particle…

Soft Condensed Matter · Physics 2018-09-12 Carolina Brito , Edan Lerner , Matthieu Wyart

Using positional data from video-microscopy of a two-dimensional colloidal system and from simulations of hard discs we determine the wave-vector-dependent normal mode spring constants in the supercooled fluid and glassy state,…

Soft Condensed Matter · Physics 2012-10-26 Christian L. Klix , Florian Ebert , Fabian Weysser , Matthias Fuchs , Georg Maret , Peter Keim

The most puzzling aspect of the glass transition observed in laboratory is an apparent decoupling of dynamics from structure. In this paper we recount the implication of various theories of glass transition for the static correlation length…

Disordered Systems and Neural Networks · Physics 2017-02-08 S. Davatolhagh

Machine learning (ML) methods provide advanced means for understanding inherent patterns within large and complex datasets. Here, we employ the principal component analysis (PCA) and the diffusion map (DM) techniques to evaluate the glass…

Soft Condensed Matter · Physics 2024-07-01 Artem Glova , Mikko Karttunen

In this work, we present a new model for the interpretation of the local dynamic behavior and the mechanical reinforcement mechanism in polymer nanocomposites. The temperature dependence of the dynamics in the glassy region is described by…

Soft Condensed Matter · Physics 2019-05-16 Georgios Kritikos , Kostas Karatasos

Topological defects are typically quantified relative to ordered backgrounds. The importance of these defects to the understanding of physical phenomena including diverse equilibrium melting transitions from low temperature ordered to…

Statistical Mechanics · Physics 2019-02-19 Z. Nussinov , N. B. Weingartner , F. S. Nogueira

We investigate the characteristic length scales associated with the glass transition phenomenon. By studying an atomic glass-forming liquid in negatively curved space, for which the local order is well identified and the amount of…

Statistical Mechanics · Physics 2010-02-10 François Sausset , Gilles Tarjus

With the advent of powerful computer simulation techniques, it is time to move from the widely used knowledge-guided empirical methods to approaches driven by data science, mainly machine learning algorithms. We investigated the predictive…

Dynamical heterogeneities -- strong fluctuations near the glass transition -- are believed to be crucial to explain much of the glass transition phenomenology. One possible hypothesis for their origin is that they emerge from soft…

Soft Condensed Matter · Physics 2012-01-10 Karina E. Avila , Horacio E. Castillo , Azita Parsaeian

Glass-to-glass and liquid-to-liquid phase transitions were observed many years ago in bulk and confined water with or without applied pressure. It is shown that they result from the competition of two-liquid phases separated by an enthalpy…

Disordered Systems and Neural Networks · Physics 2017-03-21 Robert F Tournier