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Amorphous solids lack long-range order. Therefore identifying structural defects -- akin to dislocations in crystalline solids -- that carry plastic flow in these systems remains a daunting challenge. By comparing many different structural…

This work focuses on the microstructure of metallic deposits formed by galvanostatic electrodeposition inside a Hele-Shaw cell without both supporting electrolyte and flow. For a low applied current density j, the deposit grows under the…

Mesoscale and Nanoscale Physics · Physics 2020-11-30 Chams Kharbachi , Théo Tzedakis , Fabien Chauvet

We report structure formation in submonolayers of magnetic microparticles subjected to periodic electrostatic and magnetic excitations. Depending on the excitation parameters, we observe the formation of a rich variety of structures:…

Pattern Formation and Solitons · Physics 2009-11-10 A. Snezhko , I. S. Aranson , W. -K. Kwok

We show using computer simulations and mean field theory that a system of particles in two dimensions, when confined laterally by a pair of parallel hard walls within a quasi one dimensional channel, possesses several anomalous structural…

Soft Condensed Matter · Physics 2009-11-13 Debasish Chaudhuri , Surajit Sengupta

We study stochastic processes that generate non-growing complex networks without self-loops and multiple edges (simple graphs). The work concentrates on understanding and formulation of constraints which keep the rewiring stochastic…

Physics and Society · Physics 2009-07-10 Tomas Hruz , Michal Natora , Madhuresh Agrawal

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

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

We extend our theory of amorphous packings of hard spheres to binary mixtures and more generally to multicomponent systems. The theory is based on the assumption that amorphous packings produced by typical experimental or numerical…

Disordered Systems and Neural Networks · Physics 2015-05-13 Indaco Biazzo , Francesco Caltagirone , Giorgio Parisi , Francesco Zamponi

Instabilities and avalanches in granular flows represent hallmarks of failure: they can both disrupt industrial process flows and signal dangerous conditions, like those in grain silos and snowy mountaintops. We investigate intermittency…

Soft Condensed Matter · Physics 2025-01-06 Saeed Alborzi , Sara M. Hashmi

A statistical description of heavy particles suspended in incompressible rough self-similar flows is developed. It is shown that, differently from smooth flows, particles do not form fractal clusters. They rather distribute inhomogeneously…

Chaotic Dynamics · Physics 2007-05-23 J. Bec , M. Cencini , R. Hillerbrand

The relevant parameters at the microstructure scale that govern the macroscopic toughness of disordered brittle materials are investigated theoretically. We focus on planar crack propagation and describe the front evolution as the…

Disordered Systems and Neural Networks · Physics 2014-02-25 Vincent Démery , Laurent Ponson , Alberto Rosso

We present Diffusion Structures, a family of resilient shell structures from the eigenfunctions of a pair of novel diffusion operators. This approach is based on Michell's theorem but avoids expensive non-linear optimization with…

Graphics · Computer Science 2020-11-12 Abhishek Madan , Alec Jacobson , David I. W. Levin

Non-reciprocal systems exhibit diverse dynamical phases whose character depends on the type and degree of non-reciprocity. In this study, we theoretically investigate dynamical structures in a mixture of non-reciprocally aligning polar…

Soft Condensed Matter · Physics 2024-12-20 Kim L. Kreienkamp , Sabine H. L. Klapp

In the first two papers of this series, we characterized the structure of maximally random jammed (MRJ) sphere packings across length scales by computing a variety of different correlation functions, spectral functions, hole probabilities,…

Statistical Mechanics · Physics 2018-01-24 Michael A. Klatt , Salvatore Torquato

Complex systems have motivated continuing interest from the scientific community, leading to new concepts and methods. Growing systems represent a case of particular interest, as their topological, geometrical, and also dynamical properties…

Social and Information Networks · Computer Science 2024-05-27 Alexandre Benatti , Roberto M. Cesar , Luciano da F. Costa

Studies of random close packing of spheres have advanced our knowledge about the structure of systems such as liquids, glasses, emulsions, granular media, and amorphous solids. When these systems are confined their structural properties…

Soft Condensed Matter · Physics 2009-12-17 Kenneth W. Desmond , Eric R. Weeks

Non-equilibrium cluster-cluster aggregation of particles diffusing in or at the cell membrane has been hypothesized to lead to domains of finite size in different biological contexts such as lipid rafts, cell adhesion complexes, or…

Soft Condensed Matter · Physics 2023-08-30 Renaud Baillou , Jonas Ranft

We investigate sedimentation of model hard sphere-like colloidal dispersions confined in horizontal capillaries using laser scanning confocal microscopy, dynamical density functional theory, and Brownian dynamics computer simulations. For…

Soft Condensed Matter · Physics 2009-11-13 C. Patrick Royall , Joachim Dzubiella , Matthias Schmidt , Alfons van Blaaderen

When modeling microstructures, the computational resource requirements increase rapidly as the simulation domain becomes larger. As a result, simulating a small representative fraction under periodic boundary conditions is often a necessary…

In reliable decision-making systems based on machine learning, models have to be robust to distributional shifts or provide the uncertainty of their predictions. In node-level problems of graph learning, distributional shifts can be…

Machine Learning · Computer Science 2023-11-02 Gleb Bazhenov , Denis Kuznedelev , Andrey Malinin , Artem Babenko , Liudmila Prokhorenkova