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The metastable states of a glass are counted by adding a weak pinning field which explicitly breaks the ergodicity. Their entropy, that is the logarithm of their number, is extensive in a range of temperatures $T_G < T < T_C$ only, where…

凝聚态物理 · 物理学 2009-10-28 R. Monasson

A thermodynamic measure of the fragility of liquids has recently (Ito et al ref.1) been defined in terms of the temperature dependence of the excess entropy of liquid over crystal, scaled by the excess entropy at the glass transition…

无序系统与神经网络 · 物理学 2007-05-23 L. -M. Martinez , C. A. Angell

The characterization of the formation mechanisms of amorphous solids is a large avenue for research, since understanding its non-Arrhenius behavior is challenging to overcome. In this context, we present one path toward modeling the…

Glasses are ubiquitous in daily life and technology. However the microscopic mechanisms generating this state of matter remain subject to debate: Glasses are considered either as merely hyper-viscous liquids or as resulting from a genuine…

无序系统与神经网络 · 物理学 2016-06-14 S. Albert , Th. Bauer , M. Michl , G. Biroli , J. -P. Bouchaud , A. Loidl , P. Lunkenheimer , R. Tourbot , C. Wiertel-Gasquet , F. Ladieu

Supercooled liquids exhibit spatial heterogeneity in the dynamics of their fluctuating atomic arrangements. The length and time scales of the heterogeneous dynamics are central to the glass transition and influence nucleation and growth of…

材料科学 · 物理学 2018-05-09 Pei Zhang , Jason J. Maldonis , Ze Liu , Jan Schroers , Paul M. Voyles

We introduce a new quantity to probe the glass transition. This quantity is a linear generalized compressibility which depends solely on the positions of the particles. We have performed a molecular dynamics simulation on a glass forming…

无序系统与神经网络 · 物理学 2009-11-07 Herve M. Carruzzo , Clare C. Yu

We compute the temperature-dependent barrier for alpha-relaxations in several liquids, without adjustable parameters, using experimentally determined elastic, structural, and calorimetric data. We employ the random first order…

无序系统与神经网络 · 物理学 2013-10-17 Pyotr Rabochiy , Peter G. Wolynes , Vassiliy Lubchenko

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…

无序系统与神经网络 · 物理学 2015-06-25 Vassiliy Lubchenko , P. G. Wolynes

The viscosity of glass-forming liquids increases by many orders of magnitude if their temperature is lowered by a mere factor of 2-3 [1,2]. Recent studies suggest that this widespread phenomenon is accompanied by spatially heterogeneous…

无序系统与神经网络 · 物理学 2015-05-28 Walter Kob , Sandalo Roldan-Vargas , Ludovic Berthier

We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic heterogeneity across a broad range of temperatures and time…

软凝聚态物质 · 物理学 2024-02-27 Gerhard Jung , Giulio Biroli , Ludovic Berthier

We study the statistical mechanics of supercooled liquids when the system evolves at a temperature $T$ with a field $\epsilon$ linearly coupled to its overlap with a reference configuration of the same liquid sampled at a temperature $T_0$.…

统计力学 · 物理学 2022-04-05 Benjamin Guiselin , Ludovic Berthier , Gilles Tarjus

The unifying feature of glass formers (such as polymers, supercooled liquids, colloids, granulars, spin glasses, superconductors, ...) is a sluggish dynamics at low temperatures. Indeed, their dynamics is so slow that thermal equilibrium is…

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…

软凝聚态物质 · 物理学 2019-05-16 Georgios Kritikos , Kostas Karatasos

We study the effect of freezing the positions of a fraction $c$ of particles from an equilibrium configuration of a supercooled liquid at a temperature $T$. We show that within the Random First-Order Transition theory pinning particles…

无序系统与神经网络 · 物理学 2012-12-18 Chiara Cammarota , Giulio Biroli

Sizable glass formers feature numerous unique properties and potential applications, but many questions regarding their glass transition dynamics have not been resolved yet. Here we analyzed structural relaxation times measured as a…

软凝聚态物质 · 物理学 2024-03-08 Marzena Rams-Baron , Alfred Blazytko , Riccardo Casalini , Marian Paluch

Pinning a fraction of particles from an equilibrium configuration in supercooled liquids has been recently proposed as a way to induce a new kind of glass transition, the Random Pinning Glass Transition (RPGT). The RPGT has been predicted…

无序系统与神经网络 · 物理学 2014-10-13 Chiara Cammarota

Diffusivity, a measure for how rapidly a fluid self-mixes, shows an intimate, but seemingly fragmented, connection to thermodynamics. On one hand, the "configurational" contribution to entropy (related to the number of mechanically-stable…

统计力学 · 物理学 2007-05-23 Jeetain Mittal , Jeffrey R. Errington , Thomas M. Truskett

Understanding the fracture toughness of glasses is of prime importance for science and technology. We study it here using extensive atomistic simulations in which the interaction potential, glass transition cooling rate and loading geometry…

软凝聚态物质 · 物理学 2022-01-11 David Richard , Edan Lerner , Eran Bouchbinder

The systematic identification of temperature scales in supercooled liquids that are key to understanding those liquids' underlying glass properties, and the latter's formation-history dependence, is a challenging task. Here we study the…

软凝聚态物质 · 物理学 2021-01-05 Karina González-López , Edan Lerner

When the cooling rate $v$ is smaller than a certain material-dependent threshold, the glass transition temperature $T_g$ becomes to a certain degree the "material parameter" being nearly independent on the cooling rate. The common method to…

化学物理 · 物理学 2020-11-25 N. M. Chtchelkatchev , R. E. Ryltsev , V. Ankudinov , V. N. Ryzhov , M. Apel , P. K. Galenko