Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergo...

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Bibliographic Details
Main Authors: Joydeep Munshi, Alexander Rakowski, Benjamin H. Savitzky, Steven E. Zeltmann, Jim Ciston, Matthew Henderson, Shreyas Cholia, Andrew M. Minor, Maria K. Y. Chan, Colin Ophus
Format: Article
Language:English
Published: Nature Portfolio 2022-12-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-022-00939-9

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https://doi.org/10.1038/s41524-022-00939-9

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