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Oct 24, 2024

AI model improves 4D STEM imaging for delicate materials

Posted by in categories: robotics/AI, solar power, sustainability

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 .

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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