Bayesian Inference of Nanoparticle-Broadened X-Ray Line Profiles |
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| Authors: | Nicholas Armstrong Walter Kalceff James P Cline John E Bonevich |
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| Affiliation: | University of Technology Sydney, PO Box 123, Broadway NSW 2007, Australia;National Institute of Standards and Technology, Gaithersburg, MD 20899, USA |
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| 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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| Keywords: | Bayesian fuzzy pixel instrumental broadening inverse problem maximum entropy morphology nanoparticles size broadening size distribution x-ray line profiles |
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