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We investigate proteins within heterogeneous cell membranes where non-equilibrium phenomena arises from spatial variations in concentration and temperature. We develop simulation methods building on non-equilibrium statistical mechanics to…

Soft Condensed Matter · Physics 2025-08-28 D. Jasuja , P. J. Atzberger

Simulations of fluid flow in naturally fractured rocks have implications for several subsurface applications, including energy storage and extraction, and waste storage. We are interested in flow in discrete fracture networks, which…

Numerical Analysis · Mathematics 2018-11-14 Alessio Fumagalli , Eirik Keilegavlen , Stefano Scialò

The past decade has witnessed the development and success of coarse-grained network models of proteins for predicting many equilibrium properties related to collective modes of motion. Curiously, the results are usually robust towards the…

Molecular Networks · Quantitative Biology 2008-09-23 Canan Atilgan , Ibrahim Inanc , Ali Rana Atilgan

Within the context of linear elasticity we show that a two-terminal network of springs and masses, can respond exactly the same as a normal spring, but with a frequency dependent spring constant. As a consequence a network of such springs…

Classical Physics · Physics 2015-10-28 Graeme Milton , Pierre Seppecher

Continuum elasticity is a powerful tool applicable in a broad range of physical systems and phenomena. Yet, understanding how and on what scales material disorder may lead to the breakdown of continuum elasticity is not fully understood. We…

Soft Condensed Matter · Physics 2023-04-11 Edan Lerner , Eran Bouchbinder

In this article, we unravel an intimate relationship between two seemingly unrelated concepts: elasticity, that defines the local relations between stress and strain of deformable bodies, and topology that classifies their global shape.…

Soft Condensed Matter · Physics 2019-12-25 Denis Bartolo , David Carpentier

Predicting the behaviour of complex systems is one of the main goals of science. An important example is plastic deformation of micron-scale crystals, a process mediated by collective dynamics of dislocations, manifested as broadly…

Materials Science · Physics 2022-06-03 Marcin Mińkowski , David Kurunczi-Papp , Lasse Laurson

Dense suspensions of particles dispersed in liquids are central to industrial and geophysical processes and serve as model systems for out-of-equilibrium soft matter. At high particle concentrations, they exhibit stress-dependent rheology,…

Soft Condensed Matter · Physics 2026-03-16 Orhun Ayar , Bhargav Sriram Siddani , Ishan Srivastava , Abhinendra Singh

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…

Extra-large deformations in ultra-soft elastic materials are ubiquitous, yet systematic studies and methods to understand the mechanics of such huge strains are lacking. Here we investigate this complex problem systematically with a simple…

Materials Science · Physics 2017-01-04 Aditi Chakrabarti , Manoj K. Chaudhury , Serge Mora , Yves Pomeau

In this contribution, we present a new Materials Knowledge System framework for microstructure-sensitive predictions of effective stress--strain responses in composite materials. The model is developed for composites with a wide range of…

Materials Science · Physics 2018-12-17 Marat I. Latypov , Laszlo S. Toth , Surya R. Kalidindi

It is shown that a compound elastic structure, which displays a dynamic instability, may be designed as the union (or 'fusion') of two structures which are stable when separately analyzed. The compound elastic structure has two degrees of…

Classical Physics · Physics 2023-01-16 Marco Rossi , Andrea Piccolroaz , Davide Bigoni

We propose a general method for deriving one-dimensional models for nonlinear structures. It captures the contribution to the strain energy arising not only from the macroscopic elastic strain as in classical structural models, but also…

Applied Physics · Physics 2020-03-18 Claire Lestringant , Basile Audoly

We construct and analyze a model for a disordered linear spring network with anisotropy. The modeling is motivated by, for example, granular systems, nematic elastomers, and ultimately cytoskeletal networks exhibiting some underlying…

Soft Condensed Matter · Physics 2015-06-22 T. Zhang , J. M. Schwarz , Moumita Das

Materials characterized by spatially homogeneous elastic moduli undergo affine distortions when subjected to external stress at their boundaries, i.e., their displacements $\uv (\xv)$ from a uniform reference state grow linearly with…

Soft Condensed Matter · Physics 2009-11-11 B. A. DiDonna , T. C. Lubensky

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using…

Numerical Analysis · Mathematics 2025-07-09 Wensi Wu , Mitchell Daneker , Kevin T. Turner , Matthew A. Jolley , Lu Lu

A general procedure to investigate the elastic response and calculate the elastic constants of stressed and unstressed materials through continuum field modeling, particularly the phase field crystal (PFC) models, is presented. It is found…

Materials Science · Physics 2018-05-09 Zi-Le Wang , Zhi-Feng Huang , Zhirong Liu

The problem of characterizing the structure of an elastic network constrained to lie on a frozen curved surface appears in many areas of science and has been addressed by many different approaches, most notably, extending linear elasticity…

Biological Physics · Physics 2022-08-31 Yinan Dong , Roya Zandi , Alex Travesset

Networks of elastic beams can deform either by stretching or bending of their members. The primary mode of deformation (bending or stretching) crucially depends on the specific details of the network architecture. In order to shed light on…

Soft Condensed Matter · Physics 2016-09-23 Gérald Gurtner , Marc Durand

Effectively modeling phenomena present in highly nonlinear dynamical systems whilst also accurately quantifying uncertainty is a challenging task, which often requires problem-specific techniques. We present a novel, domain-agnostic…

Machine Learning · Statistics 2021-10-26 Thomas M. McDonald , Mauricio A. Álvarez