Comparing the power law constant (n) for mono- and bi-dispersed filled slurries: using percolation theory concepts

2020 ◽  
Vol 59 (8) ◽  
pp. 583-599
Author(s):  
Gregory A. Campbell ◽  
Jayaprakash S. Radhakrishnan ◽  
Mark D Wetzel
Keyword(s):  
2021 ◽  
Author(s):  
Shinya Kano ◽  
Harutaka Mekaru

Abstract A liquid-dependent impedance is observed by vapor condensation and percolation in the void space between nanoparticles. Under the Laplace pressure, vapor is effectively condensed into liquid to fill the nanoscale voids in an as-deposited nanoparticle film. Specifically, the transient impedance of the nanoparticle film in organic vapor is dependent on the vapor pressure and the conductivity of the condensed liquid. The response follows a power law that can be explained by the classical percolation theory. The condensed vapor gradually percolates into the void space among nanoparticles. A schematic is proposed to describe the vapor condensation and percolation dynamics among the nanoparticles. These findings offer insights into the behavior of vapor adsorbates in nanomaterial assemblies that contain void space.


2012 ◽  
Vol 26 (24) ◽  
pp. 1250156
Author(s):  
TAO FU ◽  
BO XU ◽  
YONG-AN ZHANG ◽  
YINI CHEN

We study the tolerance of scale-free networks (following a power-law distribution P(k) = c⋅kα) under degree segment protection and removal. We use percolation theory to examine analytically and numerically the critical node removal fraction pc required for the disintegration of the network as well as the critical node protection fraction ppc necessary to immunize the network against the disintegration. We show that when degree segment protection is prior to degree segment removal and 2 ≤ α ≤3, scale-free networks are quite robust due to the extremely low value of ppc. Meanwhile, if we protect a degree segment with a fixed fraction of nodes, the threshold pc has a generally downward trend as the degree sum of the segment decreases, but it is not strictly monotonic.


2014 ◽  
Author(s):  
Ashish Bhan ◽  
Animesh Ray

Can one hear the ‘sound’ of a growing network? We address the problem of recognizing the topology of evolving biological or social networks. Starting from percolation theory, we analytically prove a linear inverse relationship between two simple graph parameters—the logarithm of the average cluster size and logarithm of the ratio of the edges of the graph to the theoretically maximum number of edges for that graph—that holds for all growing power law graphs. The result establishes a novel property of evolving power-law networks in the asymptotic limit of network size. Numerical simulations as well as fitting to real-world citation co-authorship networks demonstrate that the result holds for networks of finite sizes, and provides a convenient measure of the extent to which an evolving family of networks belongs to the same power-law class.


1999 ◽  
Vol 173 ◽  
pp. 289-293 ◽  
Author(s):  
J.R. Donnison ◽  
L.I. Pettit

AbstractA Pareto distribution was used to model the magnitude data for short-period comets up to 1988. It was found using exponential probability plots that the brightness did not vary with period and that the cut-off point previously adopted can be supported statistically. Examination of the diameters of Trans-Neptunian bodies showed that a power law does not adequately fit the limited data available.


1968 ◽  
Vol 11 (1) ◽  
pp. 169-178 ◽  
Author(s):  
Alan Gill ◽  
Charles I. Berlin

The unconditioned GSR’s elicited by tones of 60, 70, 80, and 90 dB SPL were largest in the mouse in the ranges around 10,000 Hz. The growth of response magnitude with intensity followed a power law (10 .17 to 10 .22 , depending upon frequency) and suggested that the unconditioned GSR magnitude assessed overall subjective magnitude of tones to the mouse in an orderly fashion. It is suggested that hearing sensitivity as assessed by these means may be closely related to the spectral content of the mouse’s vocalization as well as to the number of critically sensitive single units in the mouse’s VIIIth nerve.


2007 ◽  
Vol 23 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Carmen Hagemeister

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.


Sign in / Sign up

Export Citation Format

Share Document