File:Bayesian inference of nanoparticle-broadened X-ray line profiles (IA jresv109n1p155).pdf
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[edit]Bayesian inference of nanoparticle-broadened X-ray line profiles
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Author |
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Title |
Bayesian inference of nanoparticle-broadened X-ray line profiles |
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Volume | 109 | |
Publisher |
National Institute of Standards and Technology |
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Description |
Journal of Research of the National Institute of Standards and Technology Subjects: nanoparticles; Bayesian; size distribution; instrumental broadening; x-ray line profiles; maximum entropy; morphology |
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Language | English | |
Publication date | January 2004 | |
Current location |
IA Collections: NISTJournalofResearch; NISTresearchlibrary; fedlink; americana |
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Accession number |
jresv109n1p155 |
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Source | ||
Permission (Reusing this file) |
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This file has been identified as being free of known restrictions under copyright law, including all related and neighboring rights. |
https://creativecommons.org/publicdomain/mark/1.0/PDMCreative Commons Public Domain Mark 1.0falsefalse
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Short title | Bayesian inference of nanoparticle-broadened X-ray line profiles |
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Image title | 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. |
Author | Armstrong |
Keywords |
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Software used | LuraDocument PDF Compressor Server 5.6.64.44 |
Conversion program | LuraDocument PDF v2.44 |
Encrypted | no |
Page size | 540 x 792 pts |
Version of PDF format | 1.4 |