Activity Number:
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552
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #320930
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View Presentation
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Title:
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A Bayesian Approach to Modeling Atomic Structural Disorder
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Author(s):
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Karl Pazdernik* and Brian J. Reich and Katharine Page
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Companies:
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and North Carolina State University and Oak Ridge National Laboratory
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Keywords:
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Bayesian ;
local structure ;
materials science ;
pair distribution function ;
Reverse Monte Carlo ;
total scattering
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Abstract:
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Functional properties explored in materials science can be determined by an understanding of the local structure and disorder. Reverse Monte Carlo is a general method of atomic structural modelling that has made it possible to generate three-dimensional structural models whose properties are consistent with experimental data but are not unique. We propose a Bayesian approach that builds upon the ideas of the Reverse Monte Carlo algorithm, provides improved estimates of the variances of atomic coordinates, and succinctly incorporates multiple data sources.
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Authors who are presenting talks have a * after their name.