Operational properties of fluctuation X-ray scattering data

Abstract

X-ray scattering images collected on timescales shorter than rotation diffusion times using a (partially) coherent beam result in a significant increase in information content in the scattered data. These measurements, named fluctuation X-ray scattering (FXS), are typically performed on an X-ray freeelectron laser (XFEL) and can provide fundamental insights into the structure of biological molecules, engineered nanoparticles or energy-related mesoscopic materials beyond what can be obtained with standard X-ray scattering techniques. In order to understand, use and validate experimental FXS data, the availability of basic data characteristics and operational properties is essential, but has been absent up to this point. In this communication, an intuitive view of the nature of FXS data and their properties is provided, the effect of FXS data on the derived structural models is highlighted, and generalizations of the Guinier and Porod laws that can ultimately be used to plan experiments and assess the quality of experimental data are presented.

Correlations in Scattered X-Ray Laser Pulses Reveal Nanoscale Structural Features of Viruses

“…2(g)]. Note that the suggested compressions of the icosahedron give the virus particle an oblate character, which is supported by a generalized Guinier analyses [57,69]. Clearly, correlation maps provide a detailed fingerprint of the whole 3D structure of a single object.…”

Local orientational order in self-assembled nanoparticle films: the role of ligand composition and salt

“…In general, É ' was found to show an asymptotic q À2 behavior, best developed for ' ¼ 4 and ' ¼ 6. In contrast, Malmerberg et al (2015) reported a q À8 dependence of the coefficients. This should thus asymptotically approach a constant value by normalization to IðqÞ 2 as done in equation (1), because IðqÞ / q À4 for spheres.…”

“…X-ray cross-correlation analysis (XCCA), also known as fluctuation X-ray scattering, has been shown to overcome this limitation. Recently, the potential of XCCA has been demonstrated by various theoretical and simulation studies on 2D systems (Altarelli et al, 2010;Kurta et al, 2012;Lehmkü hler et al, 2014;Malmerberg et al, 2015;Latychevskaia et al, 2015;Martin, 2017;Lhermitte et al, 2017) and shown experimentally for thin polymer systems and NPs (Gutt et al, 2014;Schroer et al, 2015;Liu et al, 2017;, liquid crystals (Zaluzhnyy, Kurta, Sulyanova et al, 2017), and colloids and nanocrystals (Mendez et al, 2014;Mancini et al, 2016;Schroer, Westermeier et al, 2016;Mendez et al, 2016;Zaluzhnyy, Kurta, André et al, 2017;Mancini et al, 2018). We previously measured the local orientational order of self-assembled NP films of thicknesses of up to a few micrometres by means of XCCA (Schroer et al, 2015;Lehmkü hler et al, 2018).…”

Unwarping GISAXS data

“…Fourthly, a range of sophisticated data-analysis methods could be more easily applied to GISAXS data if they were remapped to an undistorted reciprocal space. For example, modern developments in correlation methods such as angular correlation analysis (Wochner et al, 2009;Altarelli et al, 2010;Lehmkü hler et al, 2014Lehmkü hler et al, , 2018Lhermitte et al, 2017), fluctuation scattering (Chen et al, 2012;Malmerberg et al, 2015;Martin, 2017), or variance scattering (Yager & Majewski, 2014;Gommes, 2016) are not currently used in a GISAXS context. Finally, we note that healing data can be a useful pre-processing step (Liu et al, 2017), allowing such data to be used with existing data-analysis pipelines, or input into modern machine-learning methods (Kiapour et al, 2014;Wang et al, 2016Wang et al, , 2017Meister et al, 2017).…”