Researchers at Monash University have developed an artificial intelligence (AI) model that significantly improves the accuracy of four-dimensional scanning transmission electron microscopy (4D STEM) images.
Called unsupervised deep denoising, this model could be a game-changer for studying materials that are easily damaged during imaging, like those used in batteries and solar cells.
The research from Monash University’s School of Physics and Astronomy, and the Monash Center of Electron Microscopy, presents a novel machine learning method for denoising large electron microscopy datasets. The study was published in npj Computational Materials.
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