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The quantitative characterization of the degree of randomness and aggregationof surface micro and nanostructures is critical to evaluate their effects ontargeted functionalities. To this end, the methods of Point Pattern Analysis(PPA), largely used in ecology and medical imaging, seem to provide a powerfultoolset. However, the application of these techniques requires the extractionof the point pattern of nanostructures from their microscope images. In thiswork, we address the issue of the impact that Scanning Electron Microscope(SEM) image processing may have on the fundamental metric of PPA, i.e. theNearest Neighbour Index (NNI). Using as examples two typical SEM images ofpolymer micro- and nanostructures taken from secondary and backscatteredelectrons, we report the effects of the a) noise filtering and b) binarizationthreshold on the value of NNI as well as the impact of the image finite sizeeffects. Based on these results, we draw conclusions for the safe choice of SEMsettings to provide accurate measurement of nanostructure randomness throughNNI estimation.

Measuring the randomness of micro and nanostructure spatial distributions: Effects of Scanning Electron Microscope image processing and analysis