In this work we analyze the defects using ML approaches observed in different thicknesses of PSb-PDMS thin films that are solvent-annealed to a range of swelling degrees, plasma etched, and converted to silica nanopatterns, as outlined in Figure . This analysis of defects runs through a wide range of magnifications starting from defects in the lattice itself, to grains to different macro-scale phases in the film (wetting, single and double layers). The focus of this work is the quantification, prediction, and minimization of defect density at all length scales of dot forming BCP films. However, other important metrics of the BCP dot array, such as pitch, can be easily determined and the effects of the solvent vapor annealing (SVA) parameter space on pitch analyzed. Shown in Figure are dot maps of localized BCP dot pitch, where the pitch of each dot is determined by taking the mean distance of a dot and its six nearest neighbors. From both the low (Figure ) and high (Figure ) magnification maps we can see there is a clear trend of a small decrease in pitch with increasing swelling degree.