English
Related papers

Related papers: Defect screening and load transfer in minimal hard…

200 papers

Double polymer networks exhibit a striking enhancement of toughness compared to single networks, yet the microscopic mechanisms governing stress redistribution, damage evolution, and fracture remain incompletely understood. Using…

Soft Condensed Matter · Physics 2026-01-09 Magali Le Goff , Laureano Ortellado , Jiting Tian , Mehdi Bouzid , Jean-Louis Barrat , Kirsten Martens

Double network hydrogels show remarkable mechanical performance, combining high strength and fracture toughness with sufficient stiffness to bear load, despite containing only a low density of cross-linked polymer molecules in water. We…

Soft Condensed Matter · Physics 2025-10-09 Samuel B. Walker , Suzanne M. Fielding

Disordered soft materials, such as fibrous networks in biological contexts exhibit a nonlinear elastic response. We study such nonlinear behavior with a minimal model for networks on lattice geometries with simple Hookian elements with…

Soft Condensed Matter · Physics 2015-03-13 M. Sheinman , C. P. Broedersz , F. C. MacKintosh

The toughness of a polymer material can increase significantly if two networks are combined into one material. This toughening effect is a consequence of a transition from a brittle to a ductile failure response. Although this transition…

Soft Condensed Matter · Physics 2020-07-01 Justin Tauber , Simone Dussi , Jasper van der Gucht

Force transmission at large length scales is crucial for such biological functions as cell motility and morphogenesis. The networks that transmit these forces are malleable, patterned by active forces generated at the microscale by…

Biological Physics · Physics 2025-11-27 Kanaya Malakar , Albert Countryman , Bulbul Chakraborty

We study quasi-static deformation of dense granular packings. The packing is deformed by imposing external boundary conditions, which model engineering experiments such as shear and compression. We propose a two-dimensional network model of…

Optimization and Control · Mathematics 2007-05-23 K. A. Ariyawansa , Leonid Berlyand , Alexander Panchenko

We propose a deep neural network (DNN) as a fast surrogate model for local stress (and in principle strain) calculation in inhomogeneous non-linear material systems. We show that the DNN predicts the local stresses with about 3.8% mean…

Materials Science · Physics 2021-03-17 Jaber Rezaei Mianroodi , Nima H. Siboni , Dierk Raabe

Multiple polymer networks, such as double-network elastomers comprising a sacrificial and a matrix network, exhibit exceptional mechanical resilience, commonly attributed to the formation of an extended damage zone before a crack can grow.…

For thin networked materials, which are spatial discrete structures constructed by continuum components, a paradox on the effective thickness defined by the in-plane and out-of-plane stiffnesses is found, i.e. the effective thickness is not…

Applied Physics · Physics 2021-06-30 Fei Pan , Feng Zhang , Yuli Chen , Zhi Liu , Xiaoling Zheng , Bin Liu

Tunable mechanics and fracture resistance are hallmarks of biological tissues and highly desired in engineered materials. To elucidate the underlying mechanisms, we study a rigidly percolating double network (DN) made of a stiff and a…

Soft Condensed Matter · Physics 2020-08-25 Pancy Lwin , Andrew Sindermann , Leo Sutter , Thomas Wyse Jackson , Lawrence Bonassar , Itai Cohen , Moumita Das

Design and analysis of inelastic materials requires prediction of physical responses that evolve under loading. Numerical simulation of such behavior using finite element (FE) approaches can call for significant time and computational…

Materials Science · Physics 2025-07-08 Indrashish Saha , Ashwini Gupta , Lori Graham-Brady

Athermal models of disordered fibrous networks are highly useful for studying the mechanics of elastic networks composed of stiff biopolymers. The underlying network architecture is a key aspect that can affect the elastic properties of…

Soft Condensed Matter · Physics 2016-01-20 Albert James Licup , Abhinav Sharma , Fred C. MacKintosh

Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data regime. These models serve as digital twins to generate…

Machine Learning · Computer Science 2023-03-21 Laya Das , Blazhe Gjorgiev , Giovanni Sansavini

In this study, we developed an inverse analysis framework that proposes a microstructure for dual-phase (DP) steel that exhibits high strength and ductility. The inverse analysis method proposed in this study involves repeated random…

Computational Engineering, Finance, and Science · Computer Science 2024-10-15 Misato Suzuki , Kazuyuki Shizawa , Mayu Muramatsu

Twisted assemblies of filaments in ropes, cables and bundles are essential structural elements in wide use in macroscopic materials as well as within the cells and tissues of living organisms. We develop the unique, non-linear elastic…

Soft Condensed Matter · Physics 2015-05-18 Gregory M. Grason

A theory of stress fields in two-dimensional granular materials based on directed force chain networks is presented. A general equation for the densities of force chains in different directions is proposed and a complete solution is…

Condensed Matter · Physics 2009-11-07 J. E. S. Socolar , D. G. Schaeffer , P. Claudin

The most profound effect of disorder on the elastic response of solids is the nonaffinity of local displacements whereby the atoms (particles, network junctions) do not simply follow the macroscopic strain, as they do in perfect crystals,…

Soft Condensed Matter · Physics 2012-01-12 Alessio Zaccone , Jamie R. Blundell , Eugene M. Terentjev

Networks are largely used for modelling and analysing data and relations among them. Recently, it has been shown that the use of a single network may not be the optimal choice, since a single network may misses some aspects. Consequently,…

Data Structures and Algorithms · Computer Science 2020-08-05 Riccardo Dondi , Pietro Hiram Guzzi , Mohammad Mehdi Hosseinzadeh

Nature provides examples of self-assemble lightweight disordered network structures with remarkable mechanical properties which are desirable for many applications purposes but challenging to reproduce artificially. Previous experimental…

Soft Condensed Matter · Physics 2019-03-27 Daniel Rayneau-Kirkhope , Silvia Bonfanti , Stefano Zapperi

A minimal model for studying the mechanical properties of amorphous solids is a disordered network of point masses connected by unbreakable springs. At a critical value of its mean connectivity, such a network becomes fragile: it undergoes…

Soft Condensed Matter · Physics 2014-03-05 Stephan Ulrich , Nitin Upadhyaya , Bas van Opheusden , Vincenzo Vitelli
‹ Prev 1 2 3 10 Next ›