Abstract

High-resolution electron microscopy is a well-suited tool for characterizing the nanoscale structure of materials. However, the interaction of the sample and the high-energy electrons of the beam can often have a detrimental impact on the sample structure. This effect can only be alleviated by decreasing the number of electrons to which the sample is exposed but will come at the cost of a decreased signal-to-noise ratio in the resulting image. Images with low signal to noise ratios are often challenging to interpret as parts of the sample with a low interaction with the electron beam are reproduced with very low contrast. Here we suggest simple measures as alternatives to the conventional signal-to-noise ratio and investigate how these can be used to predict the interpretability of the electron microscopy images. We test the models on a sample consisting of gold nanoparticles supported on a cerium dioxide substrate. The models are evaluated based on series of images acquired at varying electron dose.

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