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1.
Phys Rev E ; 103(6-1): 062145, 2021 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-34271708

RESUMEN

We mimic random nanowire networks by the homogeneous, isotropic, and random deposition of conductive zero-width sticks onto an insulating substrate. The number density (the number of objects per unit area of the surface) of these sticks is supposed to exceed the percolation threshold, i.e., the system under consideration is a conductor. To identify any current-carrying part (the backbone) of the percolation cluster, we have proposed and implemented a modification of the well-known wall follower algorithm-one type of maze solving algorithm. The advantage of the modified algorithm is its identification of the whole backbone without visiting all the edges. The complexity of the algorithm depends significantly on the structure of the graph and varies from O(sqrt[N_{V}]) to Θ(N_{V}). The algorithm has been applied to backbone identification in networks with different number densities of conducting sticks. We have found that (i) for number densities of sticks above the percolation threshold, the strength of the percolation cluster quickly approaches unity as the number density of the sticks increases; (ii) simultaneously, the percolation cluster becomes identical to its backbone plus simplest dead ends, i.e., edges that are incident to vertices of degree 1. This behavior is consistent with the presented analytical evaluations.

2.
Phys Rev E ; 102(4-1): 042119, 2020 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-33212580

RESUMEN

Using a computer simulation, we have studied the random sequential adsorption of stiff linear k-mers onto a square lattice. Each such particle occupies k adjacent lattice sites. During deposition, the two mutually perpendicular orientations of the particles are equiprobable, hence, a macroscopically isotropic monolayer is formed. However, this monolayer is locally anisotropic, since the deposited particles tend to form domains of particles with the same orientation. Using the "excluded area" concept, we have classified lattice sites into several types and examined how the fraction of each type of lattice site varies as the number of deposited particles increases. The behaviors of these quantities have allowed us to identify the following stages of domain formation: (i) the emergence of domain seeds, (ii) the filling of domains, and (iii) densification of the domains.

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