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Title: A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials

A new statistical approach for modeling diffraction profiles is introduced, using Bayesian inference and a Markov chain Monte Carlo (MCMC) algorithm. This method is demonstrated by modeling the degenerate reflections during application of an electric field to two different ferroelectric materials: thin-film lead zirconate titanate (PZT) of composition PbZr 0.3Ti 0.7O 3and a bulk commercial PZT polycrystalline ferroelectric. Here, the new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.
Authors:
 [1] ;  [2] ;  [2] ;  [2] ;  [2] ;  [2] ;  [3] ;  [3] ;  [3] ;  [4] ;  [2]
  1. North Carolina State Univ., Raleigh, NC (United States); King Mongkut's Univ. of Technology North Bangkok, Bangkok (Thailand)
  2. North Carolina State Univ., Raleigh, NC (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  4. Georgia Inst. of Technology, Atlanta, GA (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Journal of Applied Crystallography (Online)
Additional Journal Information:
Journal Name: Journal of Applied Crystallography (Online); Journal Volume: 50; Journal Issue: 1; Journal ID: ISSN 1600-5767
Publisher:
International Union of Crystallography
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; ferroelectric materials; Bayesian inference; domain switching fraction; modeling diffraction profiles
OSTI Identifier:
1342701