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Model-independent particle species disentanglement by X-ray cross-correlation scattering.

ABSTRACT: Mixtures of different particle species are often investigated using the angular averages of the scattered X-ray intensity. The number of species is deduced by singular value decomposition methods. The full disentanglement of the data into per-species contributions requires additional knowledge about the system under investigation. We propose to exploit higher-order angular X-ray intensity correlations with a new computational protocol, which we apply to synchrotron data from two-species mixtures of two-dimensional static test nanoparticles. Without any other information besides the correlations, we demonstrate the assessment of particle species concentrations in the measured data sets, as well as the full ab initio reconstruction of both particle structures. The concept extends straightforwardly to more species and to the three-dimensional case, whereby the practical application will require the measurements to be performed at an X-ray free electron laser.

SUBMITTER: Pedrini B

PROVIDER: S-EPMC5379484 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Model-independent particle species disentanglement by X-ray cross-correlation scattering.

Pedrini B B Menzel A A Guzenko V A VA David C C Abela R R Gutt C C

Scientific reports 20170404

Mixtures of different particle species are often investigated using the angular averages of the scattered X-ray intensity. The number of species is deduced by singular value decomposition methods. The full disentanglement of the data into per-species contributions requires additional knowledge about the system under investigation. We propose to exploit higher-order angular X-ray intensity correlations with a new computational protocol, which we apply to synchrotron data from two-species mixtures ...[more]

PMID: 28374754

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