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Sphractal

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Date

2024

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Abstract

The 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.

Description

Keywords

3D, atomistic surface, box-counting, fractal dimension

Citation

URI

https://dspace-test.anu.edu.au/handle/1885/733742427

Collections

DevOps Pure Testing

Source

Advanced Theory and Simulations

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Article

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DOI

10.1002/adts.202301227

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