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Related papers: Quantifying the Structure of Disordered Materials

200 papers

The understanding and quantification of ductility in crystalline metals, which has led to their widespread and effective usage as a structural material, is lacking in metallic glasses (MGs). Here, we introduce such a framework for…

We use a structure analysis technique that quantifies cluster geometries using machine learning to identify a bicapped square antiprism (BSAP) as the nearest-neighbor cluster involved in the glass transition in Pd82Si18, a prototype…

Materials Science · Physics 2019-01-23 Jason J. Maldonis , Paul M. Voyles

We analyse the connections between structure and dynamics in two model glass-formers, using the mutual information between an initial configuration and the ensuing dynamics to compare the predictive value of different structural…

Statistical Mechanics · Physics 2014-09-05 Robert L. Jack , Andrew J. Dunleavy , C. Patrick Royall

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

It is often stated that if one is presented with a snapshot of the positions of the molecules of a glass and one of a liquid, one is unable to tell the difference. Here we argue instead that given several such snapshots taken over a…

Disordered Systems and Neural Networks · Physics 2024-02-08 Ittai Fraenkel , Jorge Kurchan , Dov Levine

Understanding material composition-structure-function relationships is of critical importance for the design and discovery of novel functional materials. While most such studies focus on individual materials, we conducted a global mapping…

Materials Science · Physics 2023-02-14 Qinyang Li , Rongzhi Dong , Nihang Fu , Sadman Sadeed Omee , Lai Wei , Jianjun Hu

Determining atomistic structures from characterization data is one of the most common yet intricate problems in materials science. Particularly in amorphous materials, proposing structures that balance realism and agreement with experiments…

Disordered Systems and Neural Networks · Physics 2026-03-25 Jiawei Guo , Daniel Schwalbe-Koda

The low temperature acoustic and thermal properties of amorphous, glassy materials are remarkably similar. All these properties are described theoretically with reasonable quantitative accuracy by assuming that the amorphous solid contains…

Disordered Systems and Neural Networks · Physics 2009-11-13 Dragoş-Victor Anghel , Dmitry Churochkin

Due to the lack of long-range order, it remains challenging to characterize the structure of disordered solids and understand the nature of the glass transition. Here we propose a new structural order parameter by taking into account…

Soft Condensed Matter · Physics 2024-08-26 Ding Xu , Qinyi Liao , Ning Xu

Enhancing the kinetic stability of glasses often necessitates deepening thermodynamic stability, which typically compromises ductility due to increased structural rigidity. Decoupling these properties remains a critical challenge for…

Materials Science · Physics 2025-12-24 Huanrong Liu , Qingan Li , Shan Zhang , Rui Su , Yunjiang Wang , Pengfei Guan

Recently determined atomistic scale structures of near-two dimensional bilayers of vitreous silica (using scanning probe and electron microscopy) allow us to refine the experimentally determined coordinates to incorporate the known local…

Disordered Systems and Neural Networks · Physics 2017-11-13 Mahdi Sadjadi , Bishal Bhattarai , D. A. Drabold , M. F. Thorpe , Mark Wilson

The physics of glasses can be studied from many viewpoints, from material scientists interested in the development of new materials to statistical physicists inventing new theoretical tools to deal with disordered systems. In these lectures…

Statistical Mechanics · Physics 2007-05-23 Ludovic Berthier

In polycrystalline materials, grain boundaries are sites of enhanced atomic motion, but the complexity of the atomic structures within a grain boundary network makes it difficult to link the structure and atomic dynamics. Here we use a…

Crystal structure prediction (CSP), which aims to predict the three-dimensional atomic arrangement of a crystal from its composition, is central to materials discovery and mechanistic understanding. However, given the composition in a unit…

Materials Science · Physics 2026-03-10 Shi Yin , Jinming Mu , Xudong Zhu , Linxin He

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

Modeling inorganic glasses requires an accurate representation of interatomic interactions, large system sizes to allow for intermediate-range structural order, and slow quenching rates to eliminate kinetically trapped structural motifs.…

Chemical Physics · Physics 2025-08-29 Debendra Meher , Nikhil V. S. Avula , Sundaram Balasubramanian

Classical particle systems characterized by continuous size polydispersity, such as colloidal materials, are not straightforwardly described using statistical mechanics, since fundamental issues may arise from particle distinguishability.…

Statistical Mechanics · Physics 2017-01-16 Misaki Ozawa , Ludovic Berthier

An exact analytical expression for the static structure factor $S(k)$ in disordered materials is derived from Fourier transformed neighbor distribution decompositions in real space, and permits to reconstruct the function $S(k)$ in an…

Materials Science · Physics 2018-10-18 M. Micoulaut

Disordered systems like liquids, gels, glasses, or granular materials are not only ubiquitous in daily life and in industrial applications but they are also crucial for the mechanical stability of cells or the transport of chemical and…

Disordered Systems and Neural Networks · Physics 2019-04-30 Zhen Zhang , Walter Kob

Twisting and stacking two copies of a 2D crystal can produce a long-wavelength periodic interference pattern known as a moir\'e pattern. Performing the same procedure with an aperiodic structure instead generates a single moir\'e spot at…

Disordered Systems and Neural Networks · Physics 2025-11-04 Aaron Dunbrack