scholarly journals SASPDF: pair distribution function analysis of nanoparticle assemblies from small-angle scattering data

2020 ◽  
Vol 53 (3) ◽  
pp. 699-709 ◽  
Author(s):  
Chia-Hao Liu ◽  
Eric M. Janke ◽  
Ruipen Li ◽  
Pavol Juhás ◽  
Oleg Gang ◽  
...  
Keyword(s):  
Distribution Function ◽  
Small Angle ◽  
Pair Distribution Function ◽  
Function Analysis ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Nanoparticle Assemblies ◽  
Angle Scattering ◽  
Pdf Analysis ◽  
Crystallite Sizes

SASPDF, a method for characterizing the structure of nanoparticle assemblies (NPAs), is presented. The method is an extension of the atomic pair distribution function (PDF) analysis to the small-angle scattering (SAS) regime. The PDFgetS3 software package for computing the PDF from SAS data is also presented. An application of the SASPDF method to characterize structures of representative NPA samples with different levels of structural order is then demonstrated. The SASPDF method quantitatively yields information such as structure, disorder and crystallite sizes of ordered NPA samples. The method was also used to successfully model the data from a disordered NPA sample. The SASPDF method offers the possibility of more quantitative characterizations of NPA structures for a wide class of samples.

scholarly journals ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis

2021 ◽  
Vol 54 (1) ◽  
Author(s):  
Karen Manalastas-Cantos ◽  
Petr V. Konarev ◽  
Nelly R. Hajizadeh ◽  
Alexey G. Kikhney ◽  
Maxim V. Petoukhov ◽  
...  
Keyword(s):  
Distribution Function ◽  
Small Angle ◽  
Small Angle Scattering ◽  
Distance Distribution ◽  
Scattering Data ◽  
Mode Analysis ◽  
Distance Distribution Function ◽  
Search Volume ◽  
Angle Scattering ◽  
Pair Distance Distribution Function

The ATSAS software suite encompasses a number of programs for the processing, visualization, analysis and modelling of small-angle scattering data, with a focus on the data measured from biological macromolecules. Here, new developments in the ATSAS 3.0 package are described. They include IMSIM, for simulating isotropic 2D scattering patterns; IMOP, to perform operations on 2D images and masks; DATRESAMPLE, a method for variance estimation of structural invariants through parametric resampling; DATFT, which computes the pair distance distribution function by a direct Fourier transform of the scattering data; PDDFFIT, to compute the scattering data from a pair distance distribution function, allowing comparison with the experimental data; a new module in DATMW for Bayesian consensus-based concentration-independent molecular weight estimation; DATMIF, an ab initio shape analysis method that optimizes the search model directly against the scattering data; DAMEMB, an application to set up the initial search volume for multiphase modelling of membrane proteins; ELLLIP, to perform quasi-atomistic modelling of liposomes with elliptical shapes; NMATOR, which models conformational changes in nucleic acid structures through normal mode analysis in torsion angle space; DAMMIX, which reconstructs the shape of an unknown intermediate in an evolving system; and LIPMIX and BILMIX, for modelling multilamellar and asymmetric lipid vesicles, respectively. In addition, technical updates were deployed to facilitate maintainability of the package, which include porting the PRIMUS graphical interface to Qt5, updating SASpy – a PyMOL plugin to run a subset of ATSAS tools – to be both Python 2 and 3 compatible, and adding utilities to facilitate mmCIF compatibility in future ATSAS releases. All these features are implemented in ATSAS 3.0, freely available for academic users at https://www.embl-hamburg.de/biosaxs/software.html.

scholarly journals Characterization of Nanomaterials with Total Scattering and Pair Distribution Function Analysis: Examples from Metal Oxide Nanochemistry

2021 ◽  
Vol 75 (5) ◽  
pp. 368-375
Author(s):  
Kirsten M. Ø. Jensen
Keyword(s):  
Distribution Function ◽  
Metal Oxide ◽  
Pair Distribution Function ◽  
Bulk Material ◽  
Function Analysis ◽  
Structure Characterization ◽  
Scattering Data ◽  
Material Structure ◽  
Total Scattering ◽  
Pdf Analysis

The development of new functional nanomaterials builds on an understanding of the intricate relation between material structure and properties. Only by knowing the atomic arrangement can the mechanisms responsible for material properties be elucidated and new materials and technologies developed. Nanomaterials challenge the crystallographic techniques often used for structure characterization, and the structure of many nanomaterials are therefore often assumed to be 'cut-outs' of the corresponding bulk material. Here, I will discuss how Pair Distribution Function (PDF) analysis of total scattering data can aid nanochemists in obtaining a structural understanding of nanoscale materials, focusing on examples from metal oxide chemistry.

DShaper: an approach for handling missing low-Qdata in pair distribution function analysis of nanostructured systems

2015 ◽  
Vol 48 (6) ◽  
pp. 1651-1659 ◽  
Author(s):  
Daniel Olds ◽  
Hsiu-Wen Wang ◽  
Katharine Page
Keyword(s):  
Distribution Function ◽  
Pair Distribution Function ◽  
Shape Function ◽  
Function Analysis ◽  
Data Fitting ◽  
Scattering Data ◽  
Bulk Materials ◽  
Angle Scattering ◽  
Nanostructured Systems ◽  
Feature Information

This article discusses the potential problems and currently available solutions in modeling powder-diffraction-based pair distribution function (PDF) data from systems where morphological feature information content includes distances in the nanometre length scale, such as finite nanoparticles, nanoporous networks and nanoscale precipitates in bulk materials. The implications of an experimental finite minimumQvalue are reviewed by simulation, which also demonstrates the advantages of combining PDF data with small-angle scattering data. A simple Fortran90 code,DShaper, is introduced, which may be incorporated into PDF data fitting routines in order to approximate the so-called `shape function' for any atomistic model.

Influence of neglected small-angle scattering in radial distribution function analysis

1971 ◽  
Vol 4 (4) ◽  
pp. 277-283 ◽  
Author(s):  
G. S. Cargill
Keyword(s):  
Distribution Function ◽  
Radial Distribution Function ◽  
Radial Distribution ◽  
Small Angle ◽  
Function Analysis ◽  
Small Angle Scattering ◽  
Density Fluctuations ◽  
Atomic Density ◽  
X Ray ◽  
Angle Scattering

Materials containing inhomogeneities (density-fluctuations) of much greater than atomic size produce scattering at very small angles, which may go unobserved in many X-ray, electron, and neutron scattering experiments. For liquids and for amorphous and polycrystalline solids composed of one atomic species, an approximate expression for the reduced radial distribution function obtained from intensity measurements which neglect the small-angle scattering is shown to be Gexp(r) = 4πr{ρ(r) − ρ0[1 + (\overline {\eta^2}η2(ω)/ρ0 2)γ(ω, r)]} where ρ(r) is the atomic distribution function, ρ0 is the average atomic density, \overline {\eta^2}(ω) is the average square of atomic density fluctuations, γ(ω,r) is the density fluctuation correlation function, and ω is a volume element larger than the average atomic volume but smaller than the scale of long-range density fluctuations. This expression is also valid for systems composed of more than one type of atom where ρ(r) is a weighted average of pair distribution functions and [\overline {\eta^2}(ω)/ρ0 2]γ(ω,r) for X-ray scattering describes electron density fluctuations The neglect of small-angle scattering gives rise to a G exp(r) which appears, from its slope at small r, to correspond to a material of greater average atomic density ρ0,exp than that of the sample being studied. These results are illustrated by application to fluid argon (ρ0,exp/ρ0 = 1.17 near the critical point), to amorphous silicon (ρ0,exp/ρ0 = 1.13), and to phase separated PbO–B2O3 glasses (ρ0,exp/ρ0 = 1.07 for 24 wt. % PbO).

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.

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