Morphology-dependent random binary fragmentation of in silico fractal-like agglomerates

TL;DR

This study investigates how the shape and structure of fractal-like agglomerates influence their binary fragmentation patterns, revealing a universal distribution dependent on initial fractal dimension.

Contribution

It introduces a numerical method to analyze morphology-dependent fragmentation and derives a universal fragment distribution based on initial structure.

Findings

Fragment size distributions are U-shaped and depend on morphology.

Clusters tend to split into dissimilar fragments, becoming more uniform with decreasing fractal dimension.

A beta distribution accurately models the fragment size distribution.

Abstract

Linear binary fragmentation of synthetic fractal-like agglomerates composed of spherical, equal-size, touching monomers is numerically investigated. Agglomerates of different morphologies are fragmented via random bond removal. The fragmentation algorithm relies on mapping each agglomerate onto an adjacency matrix. The numerically-determined fragment size distributions are U-shaped, clusters break predominantly into two largely dissimilar fragments, becoming more uniform as the fractal dimension decreases. A symmetric beta distribution reproduces the fragment distribution rather accurately. Its exponent depends on the structure (fractal dimension) and number of monomers of the initial agglomerate. A universal fragment distribution, a function only of the initial fractal dimension, is derived by requiring that it satisfy the fragmentation conversation laws and the straight-chain limit. We argue that the fragmentation rate is proportional to the initial agglomerate size.