Chemical reactions and phase transformations underpin phenomena ranging from cosmological processes, to the emergence of life on Earth, to modern technologies and are therefore of tremendous interest for both basic and applied sciences. Here I provide a review of recent advancements in the intersection between computational mathematics, material science & chemical engineering. Fast Fourier Transforms were used to label the data in an automated & reliable manner. Deep learning was used to map breeches in lattice periodicity to atomic defects in Mo-doped WS2 -- effectively identifying atomic defects in the data. A Gaussian Mixture Model was then used to probabilistically cluster defects.