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

Thanakorn Iamsasri; Jonathon Guerrier; Giovanni Esteves; Chris M. Fancher; Alyson G. Wilson; Ralph C. Smith; Elizabeth A. Paisley; Raegan Johnson-Wilke; Jon F. Ihlefeld; Nazanin Bassiri-Gharb; Jacob L. Jones

doi:10.1107/S1600576716020057

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

Thanakorn Iamsasri, Jonathon Guerrier, Giovanni Esteves, Chris M. Fancher, Alyson G. Wilson, Ralph C. Smith, Elizabeth A. Paisley, Raegan Johnson-Wilke, Jon F. Ihlefeld, Nazanin Bassiri-Gharb, Jacob L. Jones

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

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_0.7O₃ and a bulk commercial PZT polycrystalline ferroelectric. The new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.

Original language	English
Pages (from-to)	211-220
Number of pages	10
Journal	Journal of Applied Crystallography
Volume	50
Issue number	1
DOIs	https://doi.org/10.1107/S1600576716020057
State	Published - Feb 1 2017
Externally published	Yes

Keywords

Bayesian inference
domain switching fraction
ferroelectric materials
modeling diffraction profiles

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10.1107/S1600576716020057

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Iamsasri, T., Guerrier, J., Esteves, G., Fancher, C. M., Wilson, A. G., Smith, R. C., Paisley, E. A., Johnson-Wilke, R., Ihlefeld, J. F., Bassiri-Gharb, N., & Jones, J. L. (2017). A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials. Journal of Applied Crystallography, 50(1), 211-220. https://doi.org/10.1107/S1600576716020057

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abstract = "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 PbZr0.3Ti0.7O3 and a bulk commercial PZT polycrystalline ferroelectric. The new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.",

keywords = "Bayesian inference, domain switching fraction, ferroelectric materials, modeling diffraction profiles",

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AU - Iamsasri, Thanakorn

AU - Guerrier, Jonathon

AU - Esteves, Giovanni

AU - Fancher, Chris M.

AU - Wilson, Alyson G.

AU - Smith, Ralph C.

AU - Paisley, Elizabeth A.

AU - Johnson-Wilke, Raegan

AU - Ihlefeld, Jon F.

AU - Bassiri-Gharb, Nazanin

AU - Jones, Jacob L.

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AB - 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 PbZr0.3Ti0.7O3 and a bulk commercial PZT polycrystalline ferroelectric. The new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.

KW - Bayesian inference

KW - domain switching fraction

KW - ferroelectric materials

KW - modeling diffraction profiles

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

Abstract

Keywords

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