A superbright X-ray laboratory microsource empowered by a novel restoration algorithm

Abstract

The properties of nanoscale materials vary with the size and shape of the building blocks, which can be measured by (grazing-incidence) small-angle X-ray scattering along with the mutual positions of the nanoparticles. The accuracy in the determination of such parameters is dependent on the signal-to-noise ratio of the X-ray scattering pattern and on the visibility of the interference fringes. Here, a first-generation-synchrotron-class X-ray laboratory microsource was used in combination with a new restoration algorithm to probe nanoscale-assembled superstructures. The proposed algorithm, based on a maximum likelihood approach, allows one to deconvolve the beam-divergence effects from data and to restore, at least partially, missing data cut away by the beam stopper. It is shown that the combination of a superbright X-ray laboratory microsource with the data-restoring method allows a virtual enhancement of the instrument brilliance, improving signal-to-noise ratio and fringe visibility and reaching levels of performance comparable to third-generation synchrotron radiation beamlines.