Comparison of iterative desmearing procedures for one-dimensional small-angle scattering data

2011 ◽  
Vol 44 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Thomas Vad ◽  
Wiebke F. C. Sager
Keyword(s):  
Small Angle ◽  
Incident Beam ◽  
Scattering Data ◽  
Data Sets ◽  
Convergence Criteria ◽  
Small Momentum Transfer ◽  
One Dimensional ◽  
Noise Filter ◽  
Large Numbers ◽  
Angle Scattering

Two simple iterative desmearing procedures – the Lake algorithm and the Van Cittert method – have been investigated by introducing different convergence criteria using both synthetic and experimental small-angle neutron scattering data. Implementing appropriate convergence criteria resulted in stable and reliable solutions in correcting resolution errors originating from instrumental smearing,i.e.finite collimation and polychromaticity of the incident beam. Deviations at small momentum transfer for concentrated ensembles of spheres encountered in earlier studies are not observed. Amplification of statistical errors can be reduced by applying a noise filter after desmearing. In most cases investigated, the modified Lake algorithm yields better results with a significantly smaller number of iterations and is, therefore, suitable for automated desmearing of large numbers of data sets.

scholarly journals The canSAS standard for storing reduced one-dimensional small-angle scattering data in XML files

2008 ◽  
Vol 64 (a1) ◽  
pp. C554-C554
Author(s):  
P.R. Jemian ◽  
A.J. Jackson ◽  
S.M. King ◽  
K.C. Littrell ◽  
A.R.J. Nelson ◽  
...  
Keyword(s):  
Small Angle ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
One Dimensional ◽  
Angle Scattering

ELLSTAT: shape modeling for solution small-angle scattering of proteins and protein complexes with automated statistical characterization

2006 ◽  
Vol 39 (5) ◽  
pp. 671-675 ◽  
Author(s):  
William T. Heller
Keyword(s):  
Small Angle ◽  
Protein Complexes ◽  
Structural Parameters ◽  
Shape Modeling ◽  
Scattering Data ◽  
Model Parameters ◽  
Data Sets ◽  
Statistical Characterization ◽  
X Ray ◽  
Angle Scattering

A method is presented for constructing one- and two-ellipsoid, core-shell-ellipsoid, cylinder and ellipsoid-plus-cylinder models from small-angle X-ray and neutron scattering data that calculates statistics on the resulting structural parameters. The method, implemented in the softwareELLSTAT, is capable of simultaneously fitting against several data sets and calculates averages, standard deviations and coefficients of linear correlation between the structural parameters of the resulting models. In this way, an improved understanding of the extent of the variability in and the interdependency between the model parameters that fit the input scattering data is developed, thereby providing a measure of the uniqueness of the models.

Small-angle scattering data analysis inGSAS-II

2014 ◽  
Vol 47 (5) ◽  
pp. 1784-1789 ◽  
Author(s):  
Robert B. Von Dreele
Keyword(s):  
Small Angle ◽  
General Structure ◽  
Scattering Data ◽  
Modeling Tools ◽  
One Dimensional ◽  
Angle Scattering ◽  
Entire Experiment ◽  
Analysis System ◽  
The One ◽  
Dilute Limit

TheGeneral Structure Analysis System II(GSAS-II) now contains modules for the analysis of small-angle X-ray scattering data. This includes processing of two-dimensional images to create corrected one-dimensional patterns, analysisviamaximum entropy or total nonnegative least-squares methods of the size distribution, assuming polydispersity, in the dilute limit, and modeling of the one-dimensional data with combinations of Guinier/Porod, Porod, both dilute and condensed populations of scattering objects, and Bragg scattering components; slit smearing corrections can be applied where needed.GSAS-IIcan apply these modeling tools over a sequence of data collected while some experimental condition is varied. This sequential refinement result can then be subjected to a post refinement analysis to determine global parameters encompassing the entire experiment.

Estimation of the density distribution from small-angle scattering data

2016 ◽  
Vol 49 (3) ◽  
pp. 856-865 ◽  
Author(s):  
Steen Hansen
Keyword(s):  
Experimental Data ◽  
Density Distribution ◽  
Small Angle ◽  
Small Angle Scattering ◽  
Single Step ◽  
Scattering Data ◽  
Maximum Dimension ◽  
Acta Cryst ◽  
One Dimensional ◽  
Angle Scattering

The one-dimensional density distribution for symmetrical scatterers is estimated from small-angle scattering data. The symmetry of the scatterers may be one dimensional (lamellar), two dimensional (cylindrical) or three dimensional (spherical). Previously this problem has been treated either by a two-step approach with the distance distribution as an intermediate [Glatter (1981).J. Appl. Cryst.14, 101–108] or in a single step using spherical harmonics [Svergun, Feigin & Schedrin (1982).Acta Cryst.A38, 827–835]. A combination of these two methods is presented here, where the density distribution is estimated using constraints without the explicit use of an intermediate distribution. A maximum entropy constraint is introduced for this problem and the results are compared with the results of the conventional smoothness constraint. Bayesian methods are used for estimation of the overall noise level of the experimental data and for the maximum dimension of the density distribution. The method described is tested on both simulated and experimental data and shown to provide reliable estimates for the Guinier radius and maximum dimension. In both cases the effects of minor deviations from the assumed symmetry as well as incorrect background subtraction are studied.

scholarly journals 2017 publication guidelines for structural modelling of small-angle scattering data from biomolecules in solution: an update

2017 ◽  
Vol 73 (9) ◽  
pp. 710-728 ◽  
Author(s):  
Jill Trewhella ◽  
Anthony P. Duff ◽  
Dominique Durand ◽  
Frank Gabel ◽  
J. Mitchell Guss ◽  
...  
Keyword(s):  
Small Angle ◽  
Task Force ◽  
Data Bank ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Quality Data ◽  
Angle Scattering ◽  
Publication Guidelines ◽  
Guidelines And Recommendations

In 2012, preliminary guidelines were published addressing sample quality, data acquisition and reduction, presentation of scattering data and validation, and modelling for biomolecular small-angle scattering (SAS) experiments. Biomolecular SAS has since continued to grow and authors have increasingly adopted the preliminary guidelines. In parallel, integrative/hybrid determination of biomolecular structures is a rapidly growing field that is expanding the scope of structural biology. For SAS to contribute maximally to this field, it is essential to ensure open access to the information required for evaluation of the quality of SAS samples and data, as well as the validity of SAS-based structural models. To this end, the preliminary guidelines for data presentation in a publication are reviewed and updated, and the deposition of data and associated models in a public archive is recommended. These guidelines and recommendations have been prepared in consultation with the members of the International Union of Crystallography (IUCr) Small-Angle Scattering and Journals Commissions, the Worldwide Protein Data Bank (wwPDB) Small-Angle Scattering Validation Task Force and additional experts in the field.

A Study of Beryllium-Based Materials and Comparison of Their X-Ray Homogeneities According to Small-Angle Scattering Data

2018 ◽  
Vol 63 (6) ◽  
pp. 874-882 ◽  
Author(s):  
A. A. Semenov ◽  
V. V. Volkov ◽  
A. V. Zabrodin ◽  
V. V. Gorlevskii ◽  
M. S. Sheverdyaev ◽  
...  
Keyword(s):  
Small Angle ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
X Ray ◽  
Angle Scattering

scholarly journals Small-angle scattering data representation in SASCIF and integrative/hybrid methods dictionary

2017 ◽  
Vol 73 (a2) ◽  
pp. C1441-C1441
Author(s):  
Brinda Vallat ◽  
Benjamin Webb ◽  
John Westbrook ◽  
Andrej Sali ◽  
Helen Berman
Keyword(s):  
Small Angle ◽  
Hybrid Methods ◽  
Data Representation ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Angle Scattering

Small-angle scattering of interacting particles. II. Generalized indirect Fourier transformation under consideration of the effective structure factor for polydisperse systems

1999 ◽  
Vol 32 (2) ◽  
pp. 197-209 ◽  
Author(s):  
B. Weyerich ◽  
J. Brunner-Popela ◽  
O. Glatter
Keyword(s):  
Form Factor ◽  
Small Angle ◽  
Structure Factor ◽  
Fourier Transformation ◽  
Hard Spheres ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Model Free ◽  
Angle Scattering ◽  
The Gift

The indirect Fourier transformation (IFT) is the method of choice for the model-free evaluation of small-angle scattering data. Unfortunately, this technique is only useful for dilute solutions because, for higher concentrations, particle interactions can no longer be neglected. Thus an advanced technique was developed as a generalized version, the so-called generalized indirect Fourier transformation (GIFT). It is based on the simultaneous determination of the form factor, representing the intraparticle contributions, and the structure factor, describing the interparticle contributions. The former can be determined absolutely free from model assumptions, whereas the latter has to be calculated according to an adequate model. In this paper, various models for the structure factor are compared,e.g.the effective structure factor for polydisperse hard spheres, the averaged structure factor, the local monodisperse approximation and the decoupling approximation. Furthermore, the structure factor for polydisperse rod-like particles is presented. As the model-free evaluation of small-angle scattering data is an essential point of the GIFT technique, the use of a structure factor without any influence of the form amplitude is advisable, at least during the first evaluation procedure. Therefore, a series of simulations are performed to check the possibility of the representation of various structure factors (such as the effective structure factor for hard spheres or the structure factor for rod-like particles) by the less exact but much simpler averaged structure factor. In all the observed cases, it was possible to recover the exact form factor with a free determined parameter set for the structure factor. The resulting parameters of the averaged structure factor have to be understood as apparent model parameters and therefore have only limited physical relevance. Thus the GIFT represents a technique for the model independent evaluation of scattering data with a minimum ofa prioriinformation.

Sign in / Sign up

Export Citation Format

Share Document