Difference between revisions of "XCCA"

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'''X-ray cross-correlation analysis''' ('''XCCA''') is a suite of techniques for analyzing correlations within [[x-ray]] [[scattering]] datasets. In particular, analysis of angular correlations within the 2D detector image can be used to isolate structural information that would be lost in a conventional circular-averaged 1D curve. Thus, even for nominally isotropic materials (powder-like sample), information about local symmetry (and thus packing motifs or [[unit cell]]) can be extracted from the data.
 
'''X-ray cross-correlation analysis''' ('''XCCA''') is a suite of techniques for analyzing correlations within [[x-ray]] [[scattering]] datasets. In particular, analysis of angular correlations within the 2D detector image can be used to isolate structural information that would be lost in a conventional circular-averaged 1D curve. Thus, even for nominally isotropic materials (powder-like sample), information about local symmetry (and thus packing motifs or [[unit cell]]) can be extracted from the data.
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Angular correlation information can also be mined to reconstruct the three-dimensional [[reciprocal-space]] from individual 2D detector snapshots. That is, XCCA methods can be exploited to co-align scattering frames, registering them into the 3D [[scattering]] volume. This is conceptually similar to [[reciprocal-space mapping]], but instead of directly reconstructing reciprocal-space by merging images, this is done in a statistical sense (because the relative alignment of frames is not known).
  
 
==References==
 
==References==

Revision as of 19:11, 11 November 2016

X-ray cross-correlation analysis (XCCA) is a suite of techniques for analyzing correlations within x-ray scattering datasets. In particular, analysis of angular correlations within the 2D detector image can be used to isolate structural information that would be lost in a conventional circular-averaged 1D curve. Thus, even for nominally isotropic materials (powder-like sample), information about local symmetry (and thus packing motifs or unit cell) can be extracted from the data.

Angular correlation information can also be mined to reconstruct the three-dimensional reciprocal-space from individual 2D detector snapshots. That is, XCCA methods can be exploited to co-align scattering frames, registering them into the 3D scattering volume. This is conceptually similar to reciprocal-space mapping, but instead of directly reconstructing reciprocal-space by merging images, this is done in a statistical sense (because the relative alignment of frames is not known).

References

XCCA

Reconstruction

XFEL

  • TBD

See Also

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