Effect of Dimensionality on the Percolation Threshold of Overlapping Nonspherical Hyperparticles
Salvatore Torquato, Yang Jiao

TL;DR
This paper investigates how the percolation threshold of overlapping convex hyperparticles varies with dimension, deriving a scaling relation based on geometrical properties and testing it across various shapes and dimensions.
Contribution
It introduces a new scaling relation for the percolation threshold of nonspherical hyperparticles that leverages geometrical measures and high-dimensional behavior insights.
Findings
Scaling relation provides accurate upper bounds for percolation thresholds.
Accuracy of the scaling relation improves with increasing dimension.
Geometrical properties like volume, surface area, and mean curvature are key to the analysis.
Abstract
A set of lower bounds on the continuum percolation threshold of overlapping convex hyperparticles of general nonspherical (anisotropic) shape with a specified orientational probability distribution in -dimensional Euclidean space have been derived [S. Torquato, J. Chem. Phys. {\bf 136}, 054106 (2012)]. The simplest of these lower bounds is given by , where is the -dimensional exclusion volume of a hyperparticle and is its -dimensional volume. In order to study the effect of dimensionality on the threshold of overlapping nonspherical convex hyperparticles with random orientations here, we obtain a scaling relation for that is based on this lower bound and a conjecture that hyperspheres provide the highest threshold among all convex hyperparticle shapes for any . This scaling relation exploits the principle that…
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