Bayesian inference of nanoparticle-broadened x-ray line profiles

Armstrong, N; Kalceff, W; Cline, JP; Bonevich, JE

Bayesian inference of nanoparticle-broadened x-ray line profiles

Armstrong, N Kalceff, W Cline, JP Bonevich, JE

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Publication Type:: Journal Article
Citation:: Journal of Research of the National Institute of Standards and Technology, 2004, 109 (1), pp. 155 - 178
Issue Date:: 2004-01-01

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Field	Value	Language
dc.contributor.author	Armstrong, N	en_US
dc.contributor.author	Kalceff, W	en_US
dc.contributor.author	Cline, JP	en_US
dc.contributor.author	Bonevich, JE	en_US
dc.date.issued	2004-01-01	en_US
dc.identifier.citation	Journal of Research of the National Institute of Standards and Technology, 2004, 109 (1), pp. 155 - 178	en_US
dc.identifier.issn	1044-677X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5862
dc.description.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.	en_US
dc.relation.ispartof	Journal of Research of the National Institute of Standards and Technology	en_US
dc.relation.isbasedon	10.6028/jres.109.012	en_US
dc.subject.classification	General Science & Technology	en_US
dc.title	Bayesian inference of nanoparticle-broadened x-ray line profiles	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	109	en_US
dc.location.activity	Rotorua, New Zealand
dc.location.activity	NIST, Gaithersburg, MD
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	109	en_US

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.

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http://hdl.handle.net/10453/5862