Open AccessIdentifying Defects with Guided Algorithms in Bragg Coherent Diffractive Imaging
Author(s) -
Andrew Ulvestad,
Youssef Nashed,
G. Beutier,
M. Verdier,
S. O. Hruszkewycz,
Maxime Dupraz
Publication year - 2017
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/s41598-017-09582-7
Subject(s) - algorithm , phaser , phase retrieval , computer science , coherent diffraction imaging , a priori and a posteriori , phase (matter) , noise (video) , optics , materials science , artificial intelligence , physics , image (mathematics) , philosophy , epistemology , quantum mechanics , fourier transform
Crystallographic defects such as dislocations can significantly alter material properties and functionality. However, imaging these imperfections during operation remains challenging due to the short length scales involved and the reactive environments of interest. Bragg coherent diffractive imaging (BCDI) has emerged as a powerful tool capable of identifying dislocations, twin domains, and other defects in 3D detail with nanometer spatial resolution within nanocrystals and grains in reactive environments. However, BCDI relies on phase retrieval algorithms that can fail to accurately reconstruct the defect network. Here, we use numerical simulations to explore different guided phase retrieval algorithms for imaging defective crystals using BCDI. We explore different defect types, defect densities, Bragg peaks, and guided algorithm fitness metrics as a function of signal-to-noise ratio. Based on these results, we offer a general prescription for phasing of defective crystals with no a priori knowledge.