  Brittle fracturing of materials is common in natural and industrial processes
over a variety of length scales. Knowledge of individual particle dynamics is
vital to obtain deeper insight into the atomistic processes governing crack
propagation in such materials, yet it is challenging to obtain these details in
experiments. We propose an experimental approach where isotropic dilational
strain is applied to a densely packed monolayer of attractive colloidal
microspheres, resulting in fracture. Using brightfield microscopy and particle
tracking, we examine the microstructural evolution of the monolayer during
fracturing. Furthermore, using a quantified representation of the
microstructure in combination with a machine learning algorithm, we calculate
the likelihood of regions of the monolayer to be on a crack line, which we term
Weakness. From this analysis, we identify the most important contributions to
crack propagation and find that local density is more important than
orientational order. Our methodology and results provide a basis for further
research on microscopic processes during the fracturing process.
