Generation and structural characterization of Debye random media

Zheng Ma and Salvatore Torquato
Phys. Rev. E 102, 043310 – Published 13 October 2020

Abstract

In their seminal paper on scattering by an inhomogeneous solid, Debye and coworkers proposed a simple exponentially decaying function for the two-point correlation function of an idealized class of two-phase random media. Such Debye random media, which have been shown to be realizable, are singularly distinct from all other models of two-phase media in that they are entirely defined by their one- and two-point correlation functions. To our knowledge, there has been no determination of other microstructural descriptors of Debye random media. In this paper, we generate Debye random media in two dimensions using an accelerated Yeong-Torquato construction algorithm. We then ascertain microstructural descriptors of the constructed media, including their surface correlation functions, pore-size distributions, lineal-path function, and chord-length probability density function. Accurate semianalytic and empirical formulas for these descriptors are devised. We compare our results for Debye random media to those of other popular models (overlapping disks and equilibrium hard disks) and find that the former model possesses a wider spectrum of hole sizes, including a substantial fraction of large holes. Our algorithm can be applied to generate other models defined by their two-point correlation functions, and their other microstructural descriptors can be determined and analyzed by the procedures laid out here.

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  • Received 27 July 2020
  • Accepted 17 September 2020

DOI:https://doi.org/10.1103/PhysRevE.102.043310

©2020 American Physical Society

Physics Subject Headings (PhySH)

Interdisciplinary Physics

Authors & Affiliations

Zheng Ma

  • Department of Physics, Princeton University, Princeton, New Jersey 08544, USA

Salvatore Torquato*

  • Department of Chemistry, Department of Physics, Princeton Institute for the Science and Technology of Materials, and Program in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA

  • *torquato@electron.princeton.edu

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Vol. 102, Iss. 4 — October 2020

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