npj Computational Materials (May 2023)

Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization

  • Siddharth Maddali,
  • Travis D. Frazer,
  • Nazar Delegan,
  • Katherine J. Harmon,
  • Sean E. Sullivan,
  • Marc Allain,
  • Wonsuk Cha,
  • Alan Dibos,
  • Ishwor Poudyal,
  • Saugat Kandel,
  • Youssef S. G. Nashed,
  • F. Joseph Heremans,
  • Hoydoo You,
  • Yue Cao,
  • Stephan O. Hruszkewycz

DOI
https://doi.org/10.1038/s41524-023-01022-7
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 12

Abstract

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Abstract In this paper we demonstrated a method to reconstruct vector-valued lattice distortion fields within nanoscale crystals by optimization of a forward model of multi-reflection Bragg coherent diffraction imaging (MR-BCDI) data. The method flexibly accounts for geometric factors that arise when making BCDI measurements, is amenable to efficient inversion with modern optimization toolkits, and allows for globally constraining a single image reconstruction to multiple Bragg peak measurements. This is enabled by a forward model that emulates the multiple Bragg peaks of a MR-BCDI experiment from a single estimate of the 3D crystal sample. We present this forward model, we implement it within the stochastic gradient descent optimization framework, and we demonstrate it with simulated and experimental data of nanocrystals with inhomogeneous internal lattice displacement. We find that utilizing a global optimization approach to MR-BCDI affords a reliable path to convergence of data which is otherwise challenging to reconstruct.