skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Introduction to Pair Distribution Function Analysis

Abstract

By collecting a total scattering pattern, subtracting the non-sample background, applying corrections, and taking the Fourier transform, the real space pair distribution function can be obtained. A PDF gives the distribution of inter-atomic distances in a material and is an excellent probe of short and intermediate range structure. RMC refinements using multiple data types are an excellent method for multi-scale modeling, including the mesoscale range.

Authors:
 [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1170274
Report Number(s):
LA-UR-15-21126
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 36 MATERIALS SCIENCE

Citation Formats

King, Graham Missell. Introduction to Pair Distribution Function Analysis. United States: N. p., 2015. Web. doi:10.2172/1170274.
King, Graham Missell. Introduction to Pair Distribution Function Analysis. United States. doi:10.2172/1170274.
King, Graham Missell. Tue . "Introduction to Pair Distribution Function Analysis". United States. doi:10.2172/1170274. https://www.osti.gov/servlets/purl/1170274.
@article{osti_1170274,
title = {Introduction to Pair Distribution Function Analysis},
author = {King, Graham Missell},
abstractNote = {By collecting a total scattering pattern, subtracting the non-sample background, applying corrections, and taking the Fourier transform, the real space pair distribution function can be obtained. A PDF gives the distribution of inter-atomic distances in a material and is an excellent probe of short and intermediate range structure. RMC refinements using multiple data types are an excellent method for multi-scale modeling, including the mesoscale range.},
doi = {10.2172/1170274},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Feb 17 00:00:00 EST 2015},
month = {Tue Feb 17 00:00:00 EST 2015}
}

Technical Report:

Save / Share: