Development of a fragment kinetic Monte Carlo method for efficient\n prediction of ionic diffusion in perovskite crystals

2020/04/20 by Hiroya Nakata, Nakata, Hiroya
Materials Science · #Advanced ceramic materials synthesis #Advancements in Solid Oxide Fuel Cells #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #Ferroelectric and Piezoelectric Materials

paper · pdf · doi:10.48550/arxiv.2004.09081

openalex publication_date 2020/04/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A massively parallel kinetic Monte Carlo (kMC) approach is proposed for\nsimulating ionic migration in a crystal system by introducing the atomic\nfragmentation scheme (fragment kMC). The fragment kMC method achieved a\nreasonable parallel efficiency with 1728 central processing unit (CPU) cores,\nand the method enables the simulation of ionic diffusion in \μm-scale\nperovskite crystals. To demonstrate the feasibility of the proposed approach,\nthe fragment kMC method was applied to predict the diffusion coefficients of\nhydrogen and oxygen in SrTiO_(3-x)H_x and BaTiO_(3-x)H_x system.\nFinally, the fragment kMC method was customized for \μ-scale BaTiO₃\nsimulation under an applied bias voltage, and oxygen diffusion in BaTiO₃\nmodel was evaluated. The respective grain sizes are sub-nanometre, and we\nconclude that the proposed fragment kMC method can be applied to calculate the\nextent of ionic migration in \μ-scale materials with fully atomistic\nsimulation models at a reasonable computational cost.\n

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