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Topological data analysis (TDA) is a new emerging and powerful tool to understand the medium range structure ordering of multi-scale data. This study investigates the density anomalies observed during cooling of liquid silica from…

Materials Science · Physics 2023-10-05 Andrea Tirelli , Kousuke Nakano

Using molecular dynamics computer simulations we investigate how in silica the glass transition and the properties of the resulting glass depend on the cooling rate with which the sample is cooled. By coupling the system to a heat bath with…

Condensed Matter · Physics 2009-10-28 Katharina Vollmayr , Walter Kob , Kurt Binder

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

Due to its non-crystalline nature, the glassy state has remained one the most exciting scientific challenges. To study such materials, Molecular Dynamics (MD) simulations have been extensively used because they provide a direct view into…

Materials Science · Physics 2015-06-23 Mathieu Bauchy

Oxide glasses with a network structure are omnipresent in daily life. Often, they are regarded as isotropic materials; however, structural anisotropy can be induced through processing in mechanical fields and leads to unique materials…

Theoretical challenges in understanding the nature of glass and the glass transition remain significant open questions in statistical and condensed matter physics. As a prototypical example of complex physical systems, glasses and the…

Disordered Systems and Neural Networks · Physics 2026-01-21 Xin-Jia Zhou , Feng Yang , Xiao-Dong Yang , Lin Ma , Zhen-Wei Wu

Whereas knowledge of a crystalline material's unit cell is fundamental to understanding the material's properties and behavior, there are not obvious analogues to unit cells for disordered materials despite the frequent existence of…

Computational Geometry · Computer Science 2020-05-27 Benjamin Schweinhart , David Rodney , Jeremy Mason

The multidimensional topography of the collective potential energy function of a so-called strong glass former (silica) is analyzed by means of classical molecular dynamics calculations. Features qualitatively similar to those of fragile…

Disordered Systems and Neural Networks · Physics 2009-10-31 Philippe Jund , Remi Jullien

Measuring similarity between complex objects is a fundamental task in many scientific fields. When objects are represented as graphs, graph similarity/distance measures offer a powerful framework for quantifying structural resemblance.…

Combinatorics · Mathematics 2025-09-30 Matthias Dehmer , Izudin Redžepović , Niko Tratnik , Petra Žigert Pleteršek

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

Anomaly detection is a crucial task in complex distributed systems. A thorough understanding of the requirements and challenges of anomaly detection is pivotal to the security of such systems, especially for real-world deployment. While…

Amorphous silica (a-SiO2) exhibits unique thermo-mechanical behaviors that set it apart from other glasses. However, there is still limited understanding of how this mechanical behavior is related to the atomic structure and to the…

This article proposes a topological method that extracts hierarchical structures of various amorphous solids. The method is based on the persistence diagram (PD), a mathematical tool for capturing shapes of multiscale data. The input to the…

Whether comparing networks to each other or to random expectation, measuring dissimilarity is essential to understanding the complex phenomena under study. However, determining the structural dissimilarity between networks is an ill-defined…

Social and Information Networks · Computer Science 2018-07-26 Leo Torres , Pablo Suarez-Serrato , Tina Eliassi-Rad

We performed calorimetric studies of 26 metallic glasses and calculated the excess entropy and excess enthalpy with respect to their counterpart crystals. On this basis, we introduced a dimensionless entropy-based parameter {\sigma}scl,…

Disordered Systems and Neural Networks · Physics 2025-05-26 J. B. Cui , R. A. Konchakov , G. V. Afonin , A. S. Makarov , G. J. Lyu , J. C. Qiao , N. P. Kobelev , V. A. Khonik

Topological constraint theory has become an increasingly popular tool to predict the compositional dependence of glass properties or pinpoint promising compositions with tailored functionalities. This approach reduces complex disordered…

Disordered Systems and Neural Networks · Physics 2020-06-16 Mathieu Bauchy

The present investigation examines the relationship between structural order, diffusivity anomalies, and density anomalies in liquid silica by means of molecular dynamics simulations. We use previously defined orientational and…

Soft Condensed Matter · Physics 2009-11-07 M. S. Shell , P. G. Debenedetti , A. Z. Panagiotopoulos

Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on the ring statistics as a metric for the medium-range…

Disordered Systems and Neural Networks · Physics 2025-11-24 Achraf Atila , Yasser Bakhouch , Zhuocheng Xie

We review a model--based rather than phenomenological approach to low--temperature anomalies in glasses. Specifically, we present a solvable model inspired by spin--glass theory that exhibits both, a glassy low--temperature phase, and a…

Statistical Mechanics · Physics 2009-10-31 Reimer Kuehn , Uta Horstmann

Glasses and disordered materials are known to display anomalous features in the density of states, in the specific heat and in thermal transport. Nevertheless, in recent years, the question whether these properties are really anomalous (and…

Disordered Systems and Neural Networks · Physics 2021-03-26 Matteo Baggioli , Alessio Zaccone
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