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The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.
In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.
This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.
This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.