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_0.7O₃ 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.