The one-dimensional synthesis of the small-angle scattering pattern of high-density polyethylene

2008 ◽  
pp. 166-173 ◽  
Author(s):  
H. Meyer ◽  
H. -G. Kilian
Keyword(s):  
Small Angle ◽  
High Density Polyethylene ◽  
Small Angle Scattering ◽  
High Density ◽  
Dimensional Synthesis ◽  
Scattering Pattern ◽  
One Dimensional ◽  
Angle Scattering ◽  
The One

Resolution, truncation and smearing of the one-dimensional spin echo small-angle scattering instrument

2003 ◽  
Vol 36 (2) ◽  
pp. 333-337
Author(s):  
Peng Yuan ◽  
Jinkui Zhao
Keyword(s):  
Small Angle ◽  
Correlation Functions ◽  
Spin Echo ◽  
Small Angle Scattering ◽  
One Dimensional ◽  
Truncation Errors ◽  
Angle Scattering ◽  
The One ◽  
Neutron Momentum ◽  
Limited Coverage

The resolution of the spin echo small-angle neutron scattering (SESANS) instrument is limited by the precession Larmor fields and by the wavelength of the neutrons. It can reach to about a micrometer with thermal neutrons and to a few tens of micrometers with cold neutrons. Since a SESANS instrument will have a limited coverage in scattering angles or in neutron momentum transfers, there will be truncation errors in the measured correlation functions. These truncation errors increase with smaller scattering particles and they limit the smallest particle that can be effectively studied by the instrument. The off-plane scatterings in one-dimensional SESANS as well as the inhomogeneity of the precession fields cause smearing effects in the correlation functions. Desmearing procedures developed for the traditional small-angle scattering instruments can be used to restore the true parameters of the scattering particle.

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

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.

Molecular Shape of Fibrinogen in Solution

1975 ◽  
Author(s):  
G. Marguerie ◽  
H. Stuhrmann
Keyword(s):  
Small Angle ◽  
Molecular Shape ◽  
Globular Proteins ◽  
Small Angle Scattering ◽  
Electron Microscopic ◽  
Scattering Pattern ◽  
Angle Scattering ◽  
Neutron Small Angle Scattering

Neutron small angle scattering in various H2O/D2O mixture was carried out for investigating the structure of fibrinogen in solution. Analysis of the scattering pattern in terms of multipoles yields an overall shape which can be described by a banana-like model. The maximum segment density is only a quarter of that encountered with compact globular proteins. This suggests that fibrinogen is rather loosely packed and seems to be an intermediate representative between compact globular proteins and statistical coil. The proposed structure is compared with physicochemical and electron microscopic properties of fibrinogen.

A Method for Interpreting Small Angle Neutron Scattering Data from Quasi-Spherical Objects

1994 ◽  
Vol 376 ◽  
Author(s):  
T.M. Sabine ◽  
W.K. Bertram ◽  
L.P. Aldridge
Keyword(s):  
Neutron Scattering ◽  
Multiple Scattering ◽  
Small Angle ◽  
Small Angle Neutron Scattering ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Type Function ◽  
Scattering Pattern ◽  
Angle Scattering

ABSTRACTSmall angle scattering data are traditionally interpreted in terms of scattering patterns at the Porod and the Guinier limits. It is difficult to fit the entire scattering pattern to account for scattering from spheres because Rayleigh's formula contains oscillatory terms which are smeared out in practice by perturbations in the sizes of the scattering agents.It is proposed that a Lorenztian type function be used instead of Rayleigh's function. By using this equation it is possible to fit the entire small angle scattering pattern and obtain the correct forms of the Guinier and Porod limits.The effects of correlation and multiple scattering are also explored.

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.

Sign in / Sign up

Export Citation Format

Share Document