Kinetic Monte Carlo Simulations for Solid State Ionics: Case Studies with the MOCASSIN Program

S. Grieshammer, Sebastian Eisele
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Abstract

Kinetic Monte Carlo simulations are a useful tool to predict and analyze the ionic conductivity in crystalline materials. We present here the basic functionalities and capabilities of our recently published Monte Carlo software for solid state ionics called MOCASSIN, exemplified by simulations of several model systems and real materials. We address the simulation of tracer correlation factors for various structures, the correlation in systems with complex migration mechanisms like interstitialcy or vehicle transport, and the impact of defect interactions on ionic conductivity. Simulations of real materials include a review of oxygen vacancy migration in doped ceria, oxygen interstitial migration in La-rich melilites, and proton conduction in acceptor doped fully hydrated barium zirconate. The results reveal the impact of defect interactions on the ionic conductivity and the importance of the defect distribution. Combinations of these effects can lead to unexpected transport behavior in solid state ionic materials, especially for multiple mobile species. Kinetic Monte Carlo simulations are therefore useful to interpret experimental data which shows unexpected behavior regarding the dependence on temperature and composition.
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固态离子动力学蒙特卡罗模拟:MOCASSIN程序的案例研究
动力学蒙特卡罗模拟是预测和分析晶体材料中离子电导率的有效工具。我们在这里介绍了我们最近发布的用于固态离子的蒙特卡罗软件MOCASSIN的基本功能和能力,并通过几个模型系统和实际材料的模拟来举例说明。我们解决了各种结构的示踪剂相关因素的模拟,具有复杂迁移机制(如间隙性或车辆运输)的系统中的相关性,以及缺陷相互作用对离子电导率的影响。对真实材料的模拟包括掺杂氧化铈中的氧空位迁移,富la千英石中的氧间隙迁移,以及受体掺杂全水合锆酸钡中的质子传导。结果揭示了缺陷相互作用对离子电导率的影响以及缺陷分布的重要性。这些效应的组合可以导致固态离子材料中意想不到的传输行为,特别是对于多个移动物种。因此,动力学蒙特卡罗模拟有助于解释实验数据,这些数据显示了与温度和成分有关的意外行为。
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