scholarly journals Fully Atomistic Analysis of Diffuse X-Ray Scattering Spectra of Silicon Defects

1997 ◽  
Vol 469 ◽  
Author(s):  
K. Nordlund ◽  
P. Partyka ◽  
R. S. Averback
Keyword(s):  
Computational Method ◽  
Scattering Data ◽  
Line Profiles ◽  
Atomic Configuration ◽  
X Ray ◽  
X Ray Scattering ◽  
Scattering Spectra ◽  
Traditional Approaches ◽  
Silicon Defects ◽  
Ray Scattering

ABSTRACTDiffuse X-ray scattering is a useful method for studying defects in silicon and metals. Although the traditional approaches of analyzing experimental diffuse X-ray scattering data have given much information about the size of defects and defect clusters, they are not very well suited for determining the atomic configuration. We present a fully atomistic computational method to calculate the diffuse X-ray scattering line profile of an arbitrary atomic configuration, and compare line profiles of point defects and Frenkel pair configurations with experiment.

scholarly journals Global Small-Angle X-ray Scattering Data Analysis of Triacylglycerols in the Molten State (Part I)

2018 ◽  
Vol 122 (45) ◽  
pp. 10320-10329 ◽  
Author(s):  
Amin Sadeghpour ◽  
Marjorie Ladd Parada ◽  
Josélio Vieira ◽  
Megan Povey ◽  
Michael Rappolt
Keyword(s):  
Data Analysis ◽  
Small Angle ◽  
Scattering Data ◽  
Molten State ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

Reconstruction of viruses from solution x-ray scattering data

1995 ◽  
Author(s):  
Yibin Zheng ◽  
Peter C. Doerschuk ◽  
John E. Johnson
Keyword(s):  
Scattering Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals REGALS: a general method to deconvolve X-ray scattering data from evolving mixtures

2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando
Keyword(s):  
A Priori ◽  
Scattering Data ◽  
Biological Macromolecules ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Open Source Software Package ◽  
Saxs Analysis ◽  
Structural Methods ◽  
Ray Scattering

AbstractMixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput, or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, we introduce the REGALS method (REGularized Alternating Least Squares), which incorporates simple expectations about the data as prior knowledge and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing, and time-resolved temperature jump. Based on its performance with these challenging datasets, we anticipate that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and python and is available freely as an open-source software package.

scholarly journals Lipid Bilayer Structure Determined by the Simultaneous Analysis of Neutron and X-Ray Scattering Data

2008 ◽  
Vol 95 (5) ◽  
pp. 2356-2367 ◽  
Author(s):  
Norbert Kučerka ◽  
John F. Nagle ◽  
Jonathan N. Sachs ◽  
Scott E. Feller ◽  
Jeremy Pencer ◽  
...  
Keyword(s):  
Lipid Bilayer ◽  
Simultaneous Analysis ◽  
Scattering Data ◽  
Bilayer Structure ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering
Sign in / Sign up

Export Citation Format

Share Document