Robust X-ray angular correlations for the study of meso-structures

As self-assembling nanomaterials become more sophisticated, it is becoming increasingly important to measure the structural order of finite-sized assemblies of nano-objects. These mesoscale clusters represent an acute challenge to conventional structural probes, owing to the range of implicated size scales (10 nm to several micrometres), the weak scattering signal and the dynamic nature of meso-clusters in native solution environments. The high X-ray flux and coherence of modern synchrotrons present an opportunity to extract structural information from these challenging systems, but conventional ensemble X-ray scattering averages out crucial information about local particle configurations. Conversely, a single meso-cluster scatters too weakly to recover the full diffraction pattern. Using X-ray angular cross-correlation analysis, it is possible to combine multiple noisy measurements to obtain robust structural information. This paper explores the key theoretical limits and experimental challenges that constrain the application of these methods to probing structural order in real nanomaterials. A metric is presented to quantify the signal-to-noise ratio of angular correlations, and it is used to identify several experimental artifacts that arise. In particular, it is found that background scattering, data masking and inter-cluster interference profoundly affect the quality of correlation analyses. A robust workflow is demonstrated for mitigating these effects and extracting reliable angular correlations from realistic experimental data.

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Estimating signal and noise of time-resolved X-ray solution scattering data at synchrotrons and XFELs

Journal of Synchrotron Radiation ◽

10.1107/s1600577520002738 ◽

2020 ◽

Vol 27 (3) ◽

pp. 633-645

Author(s):

Jungmin Kim ◽

Jong Goo Kim ◽

Hosung Ki ◽

Chi Woo Ahn ◽

Hyotcherl Ihee

Keyword(s):

Quantum Noise ◽

Structural Information ◽

Signal To Noise Ratio ◽

Liquid Solution ◽

Solution Phase ◽

Scattering Data ◽

Time Resolved ◽

X Ray ◽

The Future ◽

The Difference

Elucidating the structural dynamics of small molecules and proteins in the liquid solution phase is essential to ensure a fundamental understanding of their reaction mechanisms. In this regard, time-resolved X-ray solution scattering (TRXSS), also known as time-resolved X-ray liquidography (TRXL), has been established as a powerful technique for obtaining the structural information of reaction intermediates and products in the liquid solution phase and is expected to be applied to a wider range of molecules in the future. A TRXL experiment is generally performed at the beamline of a synchrotron or an X-ray free-electron laser (XFEL) to provide intense and short X-ray pulses. Considering the limited opportunities to use these facilities, it is necessary to verify the plausibility of a target experiment prior to the actual experiment. For this purpose, a program has been developed, referred to as S-cube, which is short for a Solution Scattering Simulator. This code allows the routine estimation of the shape and signal-to-noise ratio (SNR) of TRXL data from known experimental parameters. Specifically, S-cube calculates the difference scattering curve and the associated quantum noise on the basis of the molecular structure of the target reactant and product, the target solvent, the energy of the pump laser pulse and the specifications of the beamline to be used. Employing a simplified form for the pair-distribution function required to calculate the solute–solvent cross term greatly increases the calculation speed as compared with a typical TRXL data analysis. Demonstrative applications of S-cube are presented, including the estimation of the expected TRXL data and SNR level for the future LCLS-II HE beamlines.

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Understanding the properties of energy materials from their local structure

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273314091396 ◽

2014 ◽

Vol 70 (a1) ◽

pp. C860-C860

Author(s):

Hyunjeong Kim

Keyword(s):

Structural Information ◽

Lithium Ion ◽

Structural Features ◽

Scattering Data ◽

Energy Materials ◽

X Ray ◽

Atomic Pair Distribution Function ◽

Structure Probing ◽

Atomic Pair ◽

Pdf Analysis

Numerous energy materials with improved properties often show nano- or heavily disordered structural features which are hardly characterized by the conventional crystallographic technique alone. By using the atomic pair distribution function (PDF) analysis [1]on X-ray and neutron total scattering data, we have investigated various energy materials to elucidate structural features closely linked to their properties. Some of the examples are heavily disordered V1-xTixH2 for hydrogen storage [2] and layered Li1.2Mn0.567Ni0.166Co0.067O2 cathode material for lithium ion batteries. These materials possess an intricate structure and could easily lead to misleading results if one relies on only one structure probing technique. In this talk, I will show how their structural information was extracted from the x-ray and neutron PDFs obtained at BL22XU at SPring-8 and NOVA at J-PARC, respectively and how it was used with information available from other techniques to understand the properties of these energy materials.

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X-Ray Cross-Correlation Analysis of Disordered Ensembles of Particles: Potentials and Limitations

Advances in Condensed Matter Physics ◽

10.1155/2013/959835 ◽

2013 ◽

Vol 2013 ◽

pp. 1-15 ◽

Cited By ~ 15

Author(s):

R. P. Kurta ◽

M. Altarelli ◽

I. A. Vartanyants

Keyword(s):

Correlation Analysis ◽

Disordered Systems ◽

Cross Correlation ◽

Structural Information ◽

Three Dimensional ◽

X Ray ◽

X Ray Scattering ◽

Cross Correlation Analysis ◽

2D And 3D ◽

Ray Scattering

Angular X-ray cross-correlation analysis (XCCA) is an approach to study the structure of disordered systems using the results of X-ray scattering experiments. In this paper we summarize recent theoretical developments related to the Fourier analysis of the cross-correlation functions. Results of our simulations demonstrate the application of XCCA to two- and three-dimensional (2D and 3D) disordered ensembles of particles. We show that the structure of a single particle can be recovered using X-ray data collected from a 2D disordered system of identical particles. We also demonstrate that valuable structural information about the local structure of 3D systems, inaccessible from a standard small-angle X-ray scattering experiment, can be resolved using XCCA.

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In situ small-angle X-ray scattering reveals solution phase discharge of Li–O2 batteries with weakly solvating electrolytes

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2021893118 ◽

2021 ◽

Vol 118 (14) ◽

pp. e2021893118

Author(s):

Christian Prehal ◽

Aleksej Samojlov ◽

Manfred Nachtnebel ◽

Ludek Lovicar ◽

Manfred Kriechbaum ◽

...

Keyword(s):

Structural Information ◽

Surface Film ◽

Phase Evolution ◽

Scattering Data ◽

Carbon Surface ◽

X Ray ◽

Surface Areas ◽

X Ray Scattering ◽

Ray Scattering

Electrodepositing insulating lithium peroxide (Li2O2) is the key process during discharge of aprotic Li–O2 batteries and determines rate, capacity, and reversibility. Current understanding states that the partition between surface adsorbed and dissolved lithium superoxide governs whether Li2O2 grows as a conformal surface film or larger particles, leading to low or high capacities, respectively. However, better understanding governing factors for Li2O2 packing density and capacity requires structural sensitive in situ metrologies. Here, we establish in situ small- and wide-angle X-ray scattering (SAXS/WAXS) as a suitable method to record the Li2O2 phase evolution with atomic to submicrometer resolution during cycling a custom-built in situ Li–O2 cell. Combined with sophisticated data analysis, SAXS allows retrieving rich quantitative structural information from complex multiphase systems. Surprisingly, we find that features are absent that would point at a Li2O2 surface film formed via two consecutive electron transfers, even in poorly solvating electrolytes thought to be prototypical for surface growth. All scattering data can be modeled by stacks of thin Li2O2 platelets potentially forming large toroidal particles. Li2O2 solution growth is further justified by rotating ring-disk electrode measurements and electron microscopy. Higher discharge overpotentials lead to smaller Li2O2 particles, but there is no transition to an electronically passivating, conformal Li2O2 coating. Hence, mass transport of reactive species rather than electronic transport through a Li2O2 film limits the discharge capacity. Provided that species mobilities and carbon surface areas are high, this allows for high discharge capacities even in weakly solvating electrolytes. The currently accepted Li–O2 reaction mechanism ought to be reconsidered.

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In situ small angle X-ray scattering reveals solution phase discharge of Li-O2 batteries with weakly solvating electrolytes

10.26434/chemrxiv.11447775 ◽

2020 ◽

Author(s):

Christian Prehal ◽

Aleksej Samojlov ◽

Manfred Nachtnebel ◽

Manfred Kriechbaum ◽

Heinz Amenitsch ◽

...

Keyword(s):

Structural Information ◽

Surface Film ◽

Phase Evolution ◽

Scattering Data ◽

Carbon Surface ◽

X Ray ◽

Surface Areas ◽

X Ray Scattering ◽

Ray Scattering

Electrodepositing insulating and insoluble Li2O2 is the key process during discharge of aprotic Li-O2 batteries and determines rate, capacity, and reversibility. Current understanding states that the partition between surface adsorbed and dissolved LiO2 governs whether Li2O2 grows as a conformal surface film or larger particles, leading to low or high capacities, respectively. However, governing factors for Li2O2 packing density and capacity need better understanding, requiring in situ metrologies with structural sensitivity from the atomic to sub-micron scale. Here, we establish in situ small and wide angle X-ray scattering as a suitable method to record the Li2O2 phase evolution with atomic to sub-micrometer resolution during cycling a custom-built in situ Li-O2 cell. Combined with sophisticated data analysis, SAXS allows retrieving rich quantitative structural information from complex multi-phase systems. Surprisingly, we find that features are absent that would point at a Li2O2 surface film formed via two consecutive electron transfers, even in poorly solvating electrolytes thought to be prototypical for surface growth. All scattering data can be modeled by stacks of thin Li2O2 platelets eventually forming large toroidal particles. Higher discharge overpotentials (high currents) lead to smaller Li2O2 particles, but there is no transition to an electronically passivating, conformal Li2O2 coating. This implies that mass transport of reactive species rather than electronic transport through a Li2O2 film limits the discharge capacity. Provided that species mobilities and carbon surface areas are high, this allows for high discharge capacities even in poorly solvating electrolytes. The currently accepted Li-O2 reaction mechanism ought to be reconsidered.<br>

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Machine learning deciphers structural features of RNA duplexes measured with solution X-ray scattering

IUCrJ ◽

10.1107/s2052252520008830 ◽

2020 ◽

Vol 7 (5) ◽

pp. 870-880

Author(s):

Yen-Lin Chen ◽

Lois Pollack

Keyword(s):

Machine Learning ◽

Structural Information ◽

Structural Parameters ◽

Supervised Machine Learning ◽

Scattering Data ◽

Length Scales ◽

X Ray ◽

X Ray Scattering ◽

Extreme Gradient Boosting ◽

Ray Scattering

Macromolecular structures can be determined from solution X-ray scattering. Small-angle X-ray scattering (SAXS) provides global structural information on length scales of 10s to 100s of Ångstroms, and many algorithms are available to convert SAXS data into low-resolution structural envelopes. Extension of measurements to wider scattering angles (WAXS or wide-angle X-ray scattering) can sharpen the resolution to below 10 Å, filling in structural details that can be critical for biological function. These WAXS profiles are especially challenging to interpret because of the significant contribution of solvent in addition to solute on these smaller length scales. Based on training with molecular dynamics generated models, the application of extreme gradient boosting (XGBoost) is discussed, which is a supervised machine learning (ML) approach to interpret features in solution scattering profiles. These ML methods are applied to predict key structural parameters of double-stranded ribonucleic acid (dsRNA) duplexes. Duplex conformations vary with salt and sequence and directly impact the foldability of functional RNA molecules. The strong structural periodicities in these duplexes yield scattering profiles with rich sets of features at intermediate-to-wide scattering angles. In the ML models, these profiles are treated as 1D images or features. These ML models identify specific scattering angles, or regions of scattering angles, which correspond with and successfully predict distinct structural parameters. Thus, this work demonstrates that ML strategies can integrate theoretical molecular models with experimental solution scattering data, providing a new framework for extracting highly relevant structural information from solution experiments on biological macromolecules.

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Characterizing crystalline defects in single nanoparticles from angular correlations of single-shot diffracted X-rays

IUCrJ ◽

10.1107/s205225252000144x ◽

2020 ◽

Vol 7 (2) ◽

pp. 276-286 ◽

Cited By ~ 1

Author(s):

Akinobu Niozu ◽

Yoshiaki Kumagai ◽

Toshiyuki Nishiyama ◽

Hironobu Fukuzawa ◽

Koji Motomura ◽

...

Keyword(s):

Free Electron ◽

Structural Information ◽

Single Shot ◽

X Ray Diffraction ◽

X Ray ◽

Angular Correlations ◽

Crystalline Defects ◽

X Ray Scattering ◽

Diffraction Patterns ◽

Ray Scattering

Characterizing and controlling the uniformity of nanoparticles is crucial for their application in science and technology because crystalline defects in the nanoparticles strongly affect their unique properties. Recently, ultra-short and ultra-bright X-ray pulses provided by X-ray free-electron lasers (XFELs) opened up the possibility of structure determination of nanometre-scale matter with Å spatial resolution. However, it is often difficult to reconstruct the 3D structural information from single-shot X-ray diffraction patterns owing to the random orientation of the particles. This report proposes an analysis approach for characterizing defects in nanoparticles using wide-angle X-ray scattering (WAXS) data from free-flying single nanoparticles. The analysis method is based on the concept of correlated X-ray scattering, in which correlations of scattered X-ray are used to recover detailed structural information. WAXS experiments of xenon nanoparticles, or clusters, were conducted at an XFEL facility in Japan by using the SPring-8 Ångstrom compact free-electron laser (SACLA). Bragg spots in the recorded single-shot X-ray diffraction patterns showed clear angular correlations, which offered significant structural information on the nanoparticles. The experimental angular correlations were reproduced by numerical simulation in which kinematical theory of diffraction was combined with geometric calculations. We also explain the diffuse scattering intensity as being due to the stacking faults in the xenon clusters.

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Electron crystallography of helical protein assemblies

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100149192 ◽

1993 ◽

Vol 51 ◽

pp. 672-673

Author(s):

D.L.D. Caspar ◽

D.J. DeRosier ◽

R. Diaz ◽

D.G. Morgan ◽

L.A. Melanson ◽

...

Keyword(s):

Electron Microscopy ◽

Structural Information ◽

Signal To Noise Ratio ◽

Two Dimensional ◽

X Ray Diffraction ◽

Scattered Electron ◽

Helical Structures ◽

X Ray ◽

Special Cases ◽

Helical Protein

Electron cryomicroscopy provides structural information on two dimensional crystals. Several membrane proteins have been solved to better than 4Å resolution. This class of structure has been difficult to attack by x-ray diffraction. Another class of structures that is difficult to solve by x-ray diffraction but may be amenable to electron microscopy is the helical protein assembly. Most of our knowledge of this class has come from electron microscopy although generally the work has revealed detail to a modest resolution of about 20 Å and in two special cases to about 10Å resolution. We have been trying to extend the methods for all helical structures in a manner analogous to those used for two dimensional crystals. The difference is that the scattered electron beams from helices are much weaker than those from two dimensional crystals and the signal-to-noise ratio is poorer. We have developed methods for automatically processing large numbers of particles to extract signal from noise.

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Merging in-solution X-ray and neutron scattering data allows fine structural analysis of membrane-protein detergent complexes

10.1101/324103 ◽

2018 ◽

Author(s):

Gaetan Dias-Mirandela ◽

Giulia Tamburrino ◽

Miloš T Ivanović ◽

Felix M Strnad ◽

Olwyn Byron ◽

...

Keyword(s):

Structural Analysis ◽

Membrane Protein ◽

Neutron Scattering ◽

Structural Information ◽

Scattering Data ◽

Membrane Protein Complex ◽

X Ray ◽

Ab Initio Approach ◽

Atomic Analysis ◽

Sans Data

In-solution small angle X-ray and neutron scattering (SAXS/SANS) have become popular methods to characterize the structure of membrane proteins, solubilized by either detergents or nanodiscs. SANS studies of protein-detergent complexes usually require deuterium-labelled proteins or detergents, which in turn often lead to problems in their expression or purification. Here, we report an approach whose novelty is the combined analysis of SAXS and SANS data from an unlabeled membrane protein complex in solution in two complementary ways. Firstly, an explicit atomic analysis, including both protein and detergent molecules, using the program WAXSiS which has been adapted to predict SANS data. Secondly, the use of MONSA which allows to discriminate between detergent head- and tail-groups in an ab initio approach. Our approach is readily applicable to any detergent-solubilized protein and provides more detailed structural information on protein-detergent complexes from unlabeled samples than SAXS or SANS alone.

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Simultaneous SAXS/SANS Method at D22 of ILL: Instrument Upgrade

Applied Sciences ◽

10.3390/app11135925 ◽

2021 ◽

Vol 11 (13) ◽

pp. 5925

Author(s):

Ezzeldin Metwalli ◽

Klaus Götz ◽

Tobias Zech ◽

Christian Bär ◽

Isabel Schuldes ◽

...

Keyword(s):

Structural Model ◽

Structural Information ◽

High Energy ◽

Scattering Data ◽

Background Suppression ◽

Experimental Conditions ◽

Radiation Background ◽

Saxs Data ◽

X Ray ◽

Sans Data

A customized portable SAXS instrument has recently been constructed, installed, and tested at the D22 SANS instrument at ILL. Technical characteristics of this newly established plug-and-play SAXS system have recently been reported (J. Appl. Cryst. 2020, 53, 722). An optimized lead shielding arrangement on the SAXS system and a double energy threshold X-ray detector have been further implemented to substantially suppress the unavoidable high-energy gamma radiation background on the X-ray detector. The performance of the upgraded SAXS instrument has been examined systematically by determining background suppression factors (SFs) at various experimental conditions, including different neutron beam collimation lengths and X-ray sample-to-detector distances (SDDX-ray). Improved signal-to-noise ratio SAXS data enables combined SAXS and SANS measurements for all possible experimental conditions at the D22 instrument. Both SAXS and SANS data from the same sample volume can be fitted simultaneously using a common structural model, allowing unambiguous interpretation of the scattering data. Importantly, advanced in situ/real time investigations are possible, where both the SAXS and the SANS data can reveal time-resolved complementary nanoscale structural information.

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