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The liquid structure of a glass-forming binary alloy is studied using molecular dynamics simulations. The analysis combines common neighbour analysis with the geometrical approach of Frank and Kasper to establish that the supercooled liquid…

Soft Condensed Matter · Physics 2010-03-11 Ulf R. Pedersen , Thomas B. Schrøder , Jeppe C. Dyre , Peter Harrowell

Data-driven approaches to inferring the local structures responsible for plasticity in amorphous materials have made substantial contributions to our understanding of the failure, flow, and rearrangement dynamics of supercooled fluids. Some…

Soft Condensed Matter · Physics 2023-08-22 Tomilola M. Obadiya , Daniel M. Sussman

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

Exploring structural order in disordered systems including liquids and glasses is an intriguing but challenging issue in condensed matter physics. Here we construct a new parameter based on the angular distribution function of particles and…

Soft Condensed Matter · Physics 2018-06-11 Xiunan Yang , Wei-Hua Wang , Ke Chen

Within the mode-coupling theory for idealized glass transitions, we study the evolution of structural relaxation in binary mixtures of hard spheres with size ratios $\delta$ of the two components varying between 0.5 and 1.0. We find two…

Soft Condensed Matter · Physics 2009-11-07 W. Götze , Th. Voigtmann

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…

There have been some interesting recent advances in understanding the notion of mechanical disorder in structural glasses and the statistical mechanics of these systems' low-energy excitations. Here we contribute to these advances by…

Soft Condensed Matter · Physics 2024-01-23 Tommaso Pettinari , Gustavo Düring , Edan Lerner

Glass transitions are widely observed in various types of soft matter systems. However, the physical mechanism of these transitions remains {elusive}, despite years of ambitious research. In particular, an important unanswered question is…

Disordered Systems and Neural Networks · Physics 2022-12-20 Norihiro Oyama , Shihori Koyama , Takeshi Kawasaki

Structural relaxation in binary hard spherical particles has been shown recently to exhibit a wealth of remarkable features when size disparity or mixture's composition is varied. In this paper, we test whether or not similar dynamical…

Soft Condensed Matter · Physics 2014-12-03 Wen-Sheng Xu , Zhao-Yan Sun , Li-Jia An

The anomalous behavior of liquid water is widely associated with a liquid-liquid phase transition between high- and low-density states in the supercooled regime. At the microscopic level, tetrahedral hydrogen-bond networks govern these…

Soft Condensed Matter · Physics 2026-05-04 Kohei Yoshikawa , Kokoro Shikata , Kang Kim , Nobuyuki Matubayasi

We examine the structural and dynamic properties of confined binary hard-sphere mixtures designed to mimic realizable colloidal thin films. Using computer simulations, governed by either Newtonian or overdamped Langevin dynamics, together…

Soft Condensed Matter · Physics 2015-05-01 Jonathan A. Bollinger , Avni Jain , James Carmer , Thomas M. Truskett

Data-driven models can accurately describe and predict the dynamical properties of glass-forming liquids from structural data. Accurate predictions, however, do not guarantee an understanding of the underlying physical phenomena and the key…

Statistical Mechanics · Physics 2026-03-18 Anand Sharma , Chen Liu , Misaki Ozawa , Daniele Coslovich

We study theoretically and numerically a family of multi-point dynamic susceptibilities that quantify the strength and characteristic lengthscales of dynamic heterogeneities in glass-forming materials. We use general theoretical arguments…

All liquids are topologically disordered materials; however, the degree of disorder can vary as a result of internal fluctuations in structure and topology. These fluctuations depend on both the composition and temperature of the system.…

Statistical Mechanics · Physics 2018-08-15 Katelyn A. Kirchner , Seong H. Kim , John C. Mauro

The correlation between local structure and the propensity for structural rearrangements has been widely investigated in glass forming liquids and glasses. In this paper we use the excess two-body entropy $S_2$ and tetrahedrality $\n_{tet}$…

Statistical Mechanics · Physics 2022-03-14 Saheli Mitra , Susana Marin-Aguilar , Srikanth Sastry , Frank Smallenburg , Giuseppe Foffi

Durable interest in developing a framework for the detailed structure of glassy materials has produced numerous structural descriptors that trade off between general applicability and interpretability. However, none approach the combination…

Disordered Systems and Neural Networks · Physics 2022-11-16 Thomas J. Hardin , Michael Chandross , Rahul Meena , Spencer Fajardo , Dimitris Giovanis , Ioannis G. Kevrekidis , Michael Falk , Michael Shields

Glasses remain an elusive and poorly understood state of matter. For example, it is not clear how we can design an efficient macroscopic glass former by tuning the properties of its microscopic building blocks. In this paper, we propose a…

Soft Condensed Matter · Physics 2019-02-06 Susana Marín Aguilar , Henricus H. Wensink , Giuseppe Foffi , Frank Smallenburg

The phenomenology of glass-forming liquids is often described in terms of their underlying, high-dimensional potential energy surface. In particular, the statistics of stationary points sampled as a function of temperature provides useful…

Statistical Mechanics · Physics 2021-01-06 Masanari Shimada , Daniele Coslovich , Hideyuki Mizuno , Atsushi Ikeda

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

Glass-forming liquids exhibit slow dynamics below their melting temperatures, maintaining an amorphous structure reminiscent of normal liquids. Distinguishing microscopic structures in the supercooled and high-temperature regimes remains a…

Soft Condensed Matter · Physics 2025-07-14 Kohei Yoshikawa , Kentaro Yano , Shota Goto , Kang Kim , Nobuyuki Matubayasi
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