2015
DOI: 10.1103/physreve.92.012710
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Inherently unstable networks collapse to a critical point

Abstract: Nonequilibrium systems that are driven or drive themselves towards a critical point have been studied for almost three decades. Here we present a minimalist example of such a system, motivated by experiments on collapsing active elastic networks. Our model of an unstable elastic network exhibits a collapse towards a critical point from any macroscopically connected initial configuration. Taking into account steric interactions within the network, the model qualitatively and quantitatively reproduces results of… Show more

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Cited by 8 publications
(11 citation statements)
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“…Recently, Sheinman et al [1] introduced the No-Enclave Percolation (NEP) model to explain the motordriven collapse of a model cytoskeletal system studied by Alvarado et al [2]. The NEP model, which has received a great deal of attention [3][4][5][6][7][8][9][10][11][12][13], is based upon regular random percolation in which all clusters collapse, and what remains are solid clusters that represent the gelled regions. The authors of [1] consider a region surrounded by sites of other clusters and the NEP clusters are composed of occupied sites within the region.…”
mentioning
confidence: 99%
“…Recently, Sheinman et al [1] introduced the No-Enclave Percolation (NEP) model to explain the motordriven collapse of a model cytoskeletal system studied by Alvarado et al [2]. The NEP model, which has received a great deal of attention [3][4][5][6][7][8][9][10][11][12][13], is based upon regular random percolation in which all clusters collapse, and what remains are solid clusters that represent the gelled regions. The authors of [1] consider a region surrounded by sites of other clusters and the NEP clusters are composed of occupied sites within the region.…”
mentioning
confidence: 99%
“…Previous works have suggested that network percolation drives a rigidity transition in cytoskeletal networks. [ 37 ] Here, we test the influence of connectivity and binding kinetics to understand the origin of the observed fluid‐solid transition. First, we observe that catch bonds give rise to an increase in bound motor population within a network ( Figure a), suggesting that the overall connectivity may be causing this mechanical response.…”
Section: Resultsmentioning
confidence: 99%
“…First, we observe that catch bonds give rise to an increase in bound motor population within a network ( Figure a), suggesting that the overall connectivity may be causing this mechanical response. [ 37,38 ] Since an increase in bound motors is also observed by increasing the concentration of ideal bonds, we calculate the network connectivity for networks composed of ideal and catch bonds separately in order to isolate the effects of binding kinetics on the mechanical transition. Network connectivity is calculated by counting the average number of neighboring filaments 〈 z 〉 that each filament is connected to through a motor using 〈 z 〉 = 2 N m / N f , where N m is the number of motors connecting each filament to other filaments and N f is the total number of filaments within the system (Figure 4b).…”
Section: Resultsmentioning
confidence: 99%
“…A recent discovery found that a biologically relevant active polymer network under fragmentation can self-organise itself to exhibit a scale-invariant signature of a critical system [74,75]. While the exponents observed are close to that of the static percolation universality class [76,77], the question of whether the critical phenomenon in active network actually belongs to the static percolation universality class remains unsettled [78,79,80,81].…”
Section: Discussionmentioning
confidence: 98%