Morphology-dependent random binary fragmentation of in silico fractal-like agglomerates
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.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.