Sphractal: Estimating the Fractal Dimension of Surfaces Computed from Precise Atomic Coordinates via Box‐Counting Algorithm

Author:

Ting Jonathan Yik Chang1ORCID,Wood Andrew Thomas Agars2ORCID,Barnard Amanda Susan1ORCID

Affiliation:

1. School of Computing, 145 Science Road Australian National University Canberra ACT 2601 Australia

2. Research School of Finance Actuarial Studies & Statistics, 26C Kingsley Street Australian National University Canberra ACT 2601 Australia

Abstract

AbstractThe fractal dimension of a surface allows its degree of roughness to be characterized quantitatively. However, limited effort is attempted to calculate the fractal dimension of surfaces computed from precisely known atomic coordinates from computational biomolecular and nanomaterial studies. This work proposes methods to estimate the fractal dimension of the surface of any 3D object composed of spheres, by representing the surface as either a voxelized point cloud or a mathematically exact surface, and computing its box‐counting dimension. Sphractal is published as a Python package that provides these functionalities, and its utility is demonstrated on a set of simulated palladium nanoparticle data.

Funder

National Computational Infrastructure

Publisher

Wiley

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