... to a 2D-powder diffraction pattern (simple and easy to work with). The STEMDIFF package is a key part of our 4D-STEM/PNBD method, Version 1.0 = Matlab: just a ...
The precise characterisation of the instrumental imaging properties in the form of aberration parameters constitutes an almost universal necessity in quantitative HRTEM, and is underlying most ...
This project presents a deep learning approach for identifying material phases using X-ray diffractograms (XRD) images. Leveraging the power of the VGG16 convolutional neural network, the model ...
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