Bayesian inference of metal oxide ultrathin film structure based on crystal truncation rod measurements

Masato Anada, Yoshinori Nakanishi-Ohno, Masato Okada, Tsuyoshi Kimura, Yusuke Wakabayashi

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Monte Carlo (MC)-based refinement software to analyze the atomic arrangements of perovskite oxide ultrathin films from the crystal truncation rod intensity is developed on the basis of Bayesian inference. The advantages of the MC approach are (i) it is applicable to multi-domain structures, (ii) it provides the posterior probability of structures through Bayes' theorem, which allows one to evaluate the uncertainty of estimated structural parameters, and (iii) one can involve any information provided by other experiments and theories. The simulated annealing procedure efficiently searches for the optimum model owing to its stochastic updates, regardless of the initial values, without being trapped by local optima. The performance of the software is examined with a five-unit-cell-thick LaAlO3 film fabricated on top of SrTiO3. The software successfully found the global optima from an initial model prepared by a small grid search calculation. The standard deviations of the atomic positions derived from a dataset taken at a second-generation synchrotron are ±0.02 Å for metal sites and ±0.03 Å for oxygen sites.Reverse Monte Carlo software to analyze the atomic arrangements of perovskite oxide ultrathin films from the crystal truncation rod intensity is developed on the basis of Bayesian inference.

Original languageEnglish
Pages (from-to)1611-1616
Number of pages6
JournalJournal of Applied Crystallography
Volume50
Issue number6
DOIs
Publication statusPublished - 2017 Dec

Keywords

  • Bayesian inference
  • Monte Carlo
  • crystal truncation rods
  • perovskite films

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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