纳米颗粒加宽X射线线轮廓的贝叶斯推断

Bayesian Inference of Nanoparticle-Broadened X-Ray Line Profiles.

作者信息

Armstrong Nicholas, Kalceff Walter, Cline James P, Bonevich John E

机构信息

University of Technology Sydney, PO Box 123, Broadway NSW 2007, Australia.

National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.

出版信息

J Res Natl Inst Stand Technol. 2004 Feb 1;109(1):155-178. doi: 10.6028/jres.109.012. Print 2004 Jan-Feb.

DOI:10.6028/jres.109.012

PMID:27366604

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4849618/

Abstract

A single-step, self-contained method for determining the crystallite-size distribution and shape from experimental x-ray line profile data is presented. It is shown that the crystallite-size distribution can be determined without invoking a functional form for the size distribution, determining instead the size distribution with the least assumptions by applying the Bayesian/MaxEnt method. The Bayesian/MaxEnt method is tested using both simulated and experimental CeO2 data, the results comparing favourably with experimental CeO2 data from TEM measurements.

摘要

本文提出了一种从实验X射线线形轮廓数据中确定微晶尺寸分布和形状的单步、独立方法。结果表明，无需为尺寸分布引入函数形式，而是通过应用贝叶斯/最大熵方法以最少的假设来确定微晶尺寸分布。使用模拟的和实验的CeO₂数据对贝叶斯/最大熵方法进行了测试，结果与透射电子显微镜测量得到的CeO₂实验数据相比具有优势。