Issue 29, 2022

Stiffening of under-constrained spring networks under isotropic strain

Abstract

Disordered spring networks are a useful paradigm to examine macroscopic mechanical properties of amorphous materials. Here, we study the elastic behavior of under-constrained spring networks, i.e. networks with more degrees of freedom than springs. While such networks are usually floppy, they can be rigidified by applying external strain. Recently, an analytical formalism has been developed to predict the scaling behavior of the elastic network properties close to this rigidity transition. Here we numerically show that these predictions apply to many different classes of spring networks, including phantom triangular, Delaunay, Voronoi, and honeycomb networks. The analytical predictions further imply that the shear modulus G scales linearly with isotropic stress T close to the rigidity transition. However, this seems to be at odds with recent numerical studies suggesting an exponent between G and T that is smaller than one for some network classes. Using increased numerical precision and shear stabilization, we demonstrate here that close to the transition a linear scaling, GT, holds independent of the network class. Finally, we show that our results are not or only weakly affected by finite-size effects, depending on the network class.

Graphical abstract: Stiffening of under-constrained spring networks under isotropic strain

Article information

Article type
Paper
Submitted
14 Jan 2022
Accepted
15 Jun 2022
First published
17 Jun 2022
This article is Open Access
Creative Commons BY license

Soft Matter, 2022,18, 5410-5425

Stiffening of under-constrained spring networks under isotropic strain

C. Lee and M. Merkel, Soft Matter, 2022, 18, 5410 DOI: 10.1039/D2SM00075J

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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