Topology Counts: Force Distributions in Circular Spring Networks.

Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous, and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques, we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as the mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network. Our results for 1D linear spring networks readily generalize to arbitrary dimensions.

[1]  A. C. Berry The accuracy of the Gaussian approximation to the sum of independent variates , 1941 .

[2]  Feng,et al.  Effective-medium theory of percolation on central-force elastic networks. , 1985, Physical review. B, Condensed matter.

[3]  Richard A. Davis,et al.  Time Series: Theory and Methods , 2013 .

[4]  B. M. Fulk MATH , 1992 .

[5]  P. Janmey,et al.  Strain hardening of fibrin gels and plasma clots , 1997 .

[6]  P. Janmey,et al.  Nonlinear elasticity in biological gels , 2004, Nature.

[7]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[8]  F. MacKintosh,et al.  Nonequilibrium Mechanics of Active Cytoskeletal Networks , 2007, Science.

[9]  C. Heussinger,et al.  Force distributions and force chains in random stiff fiber networks , 2007, The European physical journal. E, Soft matter.

[10]  D. Weitz,et al.  An active biopolymer network controlled by molecular motors , 2009, Proceedings of the National Academy of Sciences.

[11]  Adrian A. Husain Ark , 2010 .

[12]  Tai-De Li,et al.  Mechanics and contraction dynamics of single platelets and implications for clot stiffening. , 2011, Nature materials.

[13]  C. Broedersz,et al.  Criticality and isostaticity in fibre networks , 2010, 1011.6535.

[14]  C. Broedersz,et al.  Nonlinear effective-medium theory of disordered spring networks. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  F. MacKintosh,et al.  Molecular motors robustly drive active gels to a critically connected state , 2013, Nature Physics.

[16]  F. MacKintosh,et al.  Elastic response of filamentous networks with compliant crosslinks. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  M. Wardetzky,et al.  Elasticity of 3D networks with rigid filaments and compliant crosslinks. , 2014, Soft matter.

[18]  Margaret Nichols Trans , 2015, De-centering queer theory.